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Model: cognitivecomputations/dolphin-2.8-mistral-7b-v02 Source: Original Platform
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257
README.md
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README.md
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---
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base_model: alpindale/Mistral-7B-v0.2-hf
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language:
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- en
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license: apache-2.0
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datasets:
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- cognitivecomputations/dolphin
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- cognitivecomputations/dolphin-coder
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- cognitivecomputations/samantha-data
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- jondurbin/airoboros-2.2.1
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- teknium/openhermes-2.5
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- m-a-p/Code-Feedback
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- m-a-p/CodeFeedback-Filtered-Instruction
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model-index:
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- name: dolphin-2.8-mistral-7b-v02
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results:
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- task:
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type: text-generation
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dataset:
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type: openai_humaneval
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name: HumanEval
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metrics:
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- name: pass@1
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type: pass@1
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value: 0.469
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verified: false
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---
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# Dolphin 2.8 Mistral 7b v0.2 🐬
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By Eric Hartford and Cognitive Computations
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[](https://discord.gg/cognitivecomputations)
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Discord: https://discord.gg/cognitivecomputations
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />
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My appreciation for the sponsors of Dolphin 2.8:
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- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 10xL40S node
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- [Winston Sou](https://twitter.com/WinsonDabbles) - Along with a generous anonymous sponsor, donated a massive personally owned compute resource!
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- [Abacus AI](https://abacus.ai/) - my employer and partner in many things.
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This model is based on [Mistral-7b-v0.2](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) a new base model released by MistralAI on March 23, 2024 but they have not yet published on HuggingFace. Thanks to @alpindale for converting / publishing.
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The base model has 32k context, and the full-weights fine-tune was with 16k sequence lengths.
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It took 3 days on 10x L40S provided by [Crusoe Cloud](https://crusoe.ai/)
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Dolphin-2.8 has a variety of instruction, conversational, and coding skills.
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Dolphin is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant to any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
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Dolphin is licensed Apache 2.0. I grant permission for any use including commercial. Dolphin was trained on data generated from GPT4 among other models.
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# Evals
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```
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{
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"arc_challenge": {
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"acc,none": 0.5921501706484642,
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"acc_stderr,none": 0.014361097288449701,
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"acc_norm,none": 0.6339590443686007,
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||||
"acc_norm_stderr,none": 0.014077223108470139
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},
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"gsm8k": {
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"exact_match,strict-match": 0.4783927217589083,
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"exact_match_stderr,strict-match": 0.013759618667051773,
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"exact_match,flexible-extract": 0.5367702805155421,
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"exact_match_stderr,flexible-extract": 0.013735191956468648
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},
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"hellaswag": {
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"acc,none": 0.6389165504879506,
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"acc_stderr,none": 0.004793330525656218,
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"acc_norm,none": 0.8338976299541924,
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"acc_norm_stderr,none": 0.00371411888431746
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},
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"mmlu": {
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"acc,none": 0.6122347243982339,
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"acc_stderr,none": 0.003893774654142997
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},
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"truthfulqa_mc2": {
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"acc,none": 0.5189872652778472,
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"acc_stderr,none": 0.014901128316426086
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},
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"winogrande": {
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"acc,none": 0.7971586424625099,
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"acc_stderr,none": 0.011301439925936643
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}
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}
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```
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.0`
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```yaml
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base_model: alpindale/Mistral-7B-v0.2-hf
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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is_mistral_derived_model: true
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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datasets:
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- path: /workspace/datasets/dolphin201-sharegpt2.jsonl
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type: sharegpt
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- path: /workspace/datasets/dolphin-coder-translate-sharegpt2.jsonl
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type: sharegpt
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- path: /workspace/datasets/dolphin-coder-codegen-sharegpt2.jsonl
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type: sharegpt
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- path: /workspace/datasets/m-a-p_Code-Feedback-sharegpt.jsonl
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type: sharegpt
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- path: /workspace/datasets/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt.jsonl
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type: sharegpt
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- path: /workspace/datasets/not_samantha_norefusals.jsonl
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type: sharegpt
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- path: /workspace/datasets/openhermes2_5-sharegpt.jsonl
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type: sharegpt
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chat_template: chatml
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.001
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output_dir: /workspace/dolphin-2.8-mistral-7b
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sequence_len: 16384
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sample_packing: true
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pad_to_sequence_len: true
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wandb_project: dolphin
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wandb_entity:
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wandb_watch:
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wandb_run_id:
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wandb_log_model:
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gradient_accumulation_steps: 8
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micro_batch_size: 3
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num_epochs: 4
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adam_beta2: 0.95
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adam_epsilon: 0.00001
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max_grad_norm: 1.0
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lr_scheduler: cosine
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learning_rate: 0.000005
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optimizer: adamw_bnb_8bit
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train_on_inputs: false
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group_by_length: false
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bf16: true
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fp16: false
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tf32: false
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 10
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eval_steps: 73
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eval_table_size:
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eval_table_max_new_tokens:
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eval_sample_packing: false
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saves_per_epoch:
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save_steps: 73
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save_total_limit: 2
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debug:
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deepspeed: deepspeed_configs/zero3_bf16.json
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weight_decay: 0.1
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fsdp:
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fsdp_config:
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special_tokens:
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eos_token: "<|im_end|>"
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tokens:
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- "<|im_start|>"
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```
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</details><br>
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# workspace/dolphin-2.8-mistral-7b
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This model is a fine-tuned version of [alpindale/Mistral-7B-v0.2-hf](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4828
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-06
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- train_batch_size: 3
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- eval_batch_size: 3
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 10
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 240
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- total_eval_batch_size: 30
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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||||
|:-------------:|:-----:|:----:|:---------------:|
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| 1.1736 | 0.0 | 1 | 1.0338 |
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| 0.6106 | 0.36 | 73 | 0.5439 |
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| 0.5766 | 0.72 | 146 | 0.5171 |
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| 0.5395 | 1.06 | 219 | 0.5045 |
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| 0.5218 | 1.42 | 292 | 0.4976 |
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| 0.5336 | 1.78 | 365 | 0.4915 |
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| 0.5018 | 2.13 | 438 | 0.4885 |
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| 0.5113 | 2.48 | 511 | 0.4856 |
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| 0.5066 | 2.84 | 584 | 0.4838 |
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| 0.4967 | 3.19 | 657 | 0.4834 |
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| 0.4956 | 3.55 | 730 | 0.4830 |
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| 0.5026 | 3.9 | 803 | 0.4828 |
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### Framework versions
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- Transformers 4.40.0.dev0
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.0
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# Quants
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- [dagbs/-GGUF](https://huggingface.co/dagbs/dolphin-2.8-mistral-7b-v02-GGUF)
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- [bartowski/ExLlamaV2](https://huggingface.co/bartowski/dolphin-2.8-mistral-7b-v02-exl2)
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- [solidrust/AWQ](https://huggingface.co/solidrust/dolphin-2.8-mistral-7b-v02-AWQ)
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4
added_tokens.json
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added_tokens.json
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{
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"<|im_end|>": 32000,
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"<|im_start|>": 32001
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}
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config.json
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config.json
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{
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"_name_or_path": "alpindale/Mistral-7B-v0.2-hf",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 32000,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.40.0.dev0",
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"use_cache": false,
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"vocab_size": 32002
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}
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1
configuration.json
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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eval.sh
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eval.sh
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#!/bin/bash
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MODEL_PATH="cognitivecomputations/dolphin-2.8-mistral-7b-v02"
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MODEL_NAME="dolphin-2.8-mistral-7b-v02"
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RESULTS_PATH="/workspace/results/$MODEL_NAME"
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||||
mkdir -p "$RESULTS_PATH"
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||||
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||||
MODEL_ARGS="pretrained=$MODEL_PATH,dtype=auto"
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tasks=(
|
||||
"truthfulqa"
|
||||
"winogrande"
|
||||
"gsm8k"
|
||||
"hellaswag"
|
||||
"arc_challenge"
|
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"mmlu"
|
||||
)
|
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# Function to get the number of fewshot for a given task
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||||
get_num_fewshot() {
|
||||
case "$1" in
|
||||
"mmlu") echo 5 ;;
|
||||
"truthfulqa") echo 0 ;;
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||||
"gsm8k") echo 5 ;;
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||||
"hellaswag") echo 10 ;;
|
||||
"arc_challenge") echo 25 ;;
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"winogrande") echo 5 ;;
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*) echo 0 ;;
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||||
esac
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||||
}
|
||||
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||||
for TASK in "${tasks[@]}"; do
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lm_eval --model hf --model_args "$MODEL_ARGS" --task="$TASK" --num_fewshot "$(get_num_fewshot "$TASK")" --device cuda:0 --batch_size 8 --output_path "$RESULTS_PATH/$TASK.json"
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||||
# lm_eval --model vllm --model_args "$MODEL_ARGS" --task="$TASK" --num_fewshot "$(get_num_fewshot "$TASK")" --batch_size 8 --output_path "$RESULTS_PATH/$TASK.json"
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||||
|
||||
done
|
||||
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||||
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||||
jq -s '[.[]]' $RESULTS_PATH/*.json > $RESULTS_PATH/eval_results.json
|
||||
|
||||
huggingface-cli upload cognitivecomputations/$MODEL_NAME $RESULTS_PATH/eval_results.json
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||||
huggingface-cli upload cognitivecomputations/$MODEL_NAME eval.sh
|
||||
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||||
# docker run -it --network=host --group-add=video --ipc=host --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --device /dev/kfd --device /dev/dri -v /workspace/models/dolphin-phi-kensho:/app/model embeddedllminfo/vllm-rocm bash
|
||||
3337
eval_results.json
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3337
eval_results.json
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7
generation_config.json
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7
generation_config.json
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{
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"_from_model_config": true,
|
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"bos_token_id": 1,
|
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"do_sample": true,
|
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"eos_token_id": 2,
|
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"transformers_version": "4.40.0.dev0"
|
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}
|
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
"model.norm.weight": "model-00003-of-00003.safetensors"
|
||||
}
|
||||
}
|
||||
24
special_tokens_map.json
Normal file
24
special_tokens_map.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "</s>",
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
60
tokenizer_config.json
Normal file
60
tokenizer_config.json
Normal file
@@ -0,0 +1,60 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"add_prefix_space": true,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"32000": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"32001": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"bos_token": "<s>",
|
||||
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "</s>",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false,
|
||||
"use_fast": true
|
||||
}
|
||||
Reference in New Issue
Block a user