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Model: W-61/llama-3-8b-base-sft-hh-helpful-4xh200 Source: Original Platform
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README.md
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README.md
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---
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library_name: transformers
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base_model: meta-llama/Meta-Llama-3-8B
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tags:
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- alignment-handbook
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- generated_from_trainer
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datasets:
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- Anthropic/hh-rlhf
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model-index:
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- name: llama-3-8b-base-sft-hh-helpful-4xh200-batch-64-20260416-162101
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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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# llama-3-8b-base-sft-hh-helpful-4xh200-batch-64-20260416-162101
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the Anthropic/hh-rlhf dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1934
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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: 2e-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: 2
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- total_train_batch_size: 64
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- total_eval_batch_size: 32
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.5069 | 0.3868 | 100 | 1.4891 |
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| 1.2171 | 0.7737 | 200 | 1.1934 |
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### Framework versions
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- Transformers 4.51.0
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.21.4
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all_results.json
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all_results.json
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{
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"epoch": 0.9980657640232108,
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"eval_loss": 1.1544486284255981,
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"eval_runtime": 4.7384,
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"eval_samples": 2339,
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"eval_samples_per_second": 188.882,
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"eval_steps_per_second": 5.909,
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"total_flos": 9.517157411769549e+16,
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"train_loss": 1.5008004404777704,
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"train_runtime": 885.0234,
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"train_samples": 43598,
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"train_samples_per_second": 18.662,
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"train_steps_per_second": 0.292
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}
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"head_dim": 128,
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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": 8192,
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"mlp_bias": false,
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"model_type": "llama",
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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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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.51.0",
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"use_cache": true,
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"vocab_size": 128256
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}
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eval_results.json
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"eval_runtime": 4.7384,
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"eval_samples": 2339,
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"eval_samples_per_second": 188.882,
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"eval_steps_per_second": 5.909
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}
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generation_config.json
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"temperature": 0.6,
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"top_p": 0.9,
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"step": 258,
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"total_flos": 9.517157411769549e+16,
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"train_loss": 1.5008004404777704,
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"train_runtime": 885.0234,
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||||
"train_samples_per_second": 18.662,
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||||
"train_steps_per_second": 0.292
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||||
}
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||||
],
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||||
"logging_steps": 5,
|
||||
"max_steps": 258,
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||||
"num_input_tokens_seen": 0,
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||||
"num_train_epochs": 1,
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||||
"save_steps": 200,
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||||
"stateful_callbacks": {
|
||||
"TrainerControl": {
|
||||
"args": {
|
||||
"should_epoch_stop": false,
|
||||
"should_evaluate": false,
|
||||
"should_log": false,
|
||||
"should_save": true,
|
||||
"should_training_stop": true
|
||||
},
|
||||
"attributes": {}
|
||||
}
|
||||
},
|
||||
"total_flos": 9.517157411769549e+16,
|
||||
"train_batch_size": 8,
|
||||
"trial_name": null,
|
||||
"trial_params": null
|
||||
}
|
||||
Reference in New Issue
Block a user