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Model: mnoukhov/pythia1b-sft-tldr Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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base_model: EleutherAI/pythia-1b-deduped
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tags:
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- trl
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- sft
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- generated_from_trainer
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model-index:
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- name: pythia1b-sft-tldr
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# pythia1b-sft-tldr
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This model is a fine-tuned version of [EleutherAI/pythia-1b-deduped](https://huggingface.co/EleutherAI/pythia-1b-deduped) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3828
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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: 1e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- num_epochs: 1
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 2.5278 | 0.2007 | 183 | 2.4199 |
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| 2.4136 | 0.4013 | 366 | 2.4004 |
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| 2.3978 | 0.6020 | 549 | 2.3887 |
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| 2.3813 | 0.8026 | 732 | 2.3828 |
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### Framework versions
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- Transformers 4.41.1
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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config.json
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config.json
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{
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"_name_or_path": "EleutherAI/pythia-1b-deduped",
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"architectures": [
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"GPTNeoXForCausalLM"
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],
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"attention_bias": true,
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"attention_dropout": 0.0,
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"bos_token_id": 0,
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"classifier_dropout": 0.1,
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"eos_token_id": 0,
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"hidden_act": "gelu",
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"hidden_dropout": 0.0,
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 2048,
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"model_type": "gpt_neox",
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"num_attention_heads": 8,
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"num_hidden_layers": 16,
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"rope_scaling": null,
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"rotary_pct": 0.25,
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}
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