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--- |
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library_name: transformers |
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license: llama3.1 |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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tags: |
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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: prm_version3_full_hf |
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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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# prm_version3_full_hf |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the prm_conversations_prm_version3_math+webinstructsub-mcq+webinstructsub-oe+apps+gsm_mix_ref_hf dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1166 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.05 |
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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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| 0.1961 | 0.0461 | 500 | 0.2069 | |
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| 0.192 | 0.0921 | 1000 | 0.1930 | |
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| 0.1963 | 0.1382 | 1500 | 0.1833 | |
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| 0.1701 | 0.1843 | 2000 | 0.1748 | |
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| 0.1647 | 0.2303 | 2500 | 0.1687 | |
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| 0.1507 | 0.2764 | 3000 | 0.1630 | |
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| 0.1421 | 0.3225 | 3500 | 0.1579 | |
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| 0.1403 | 0.3685 | 4000 | 0.1528 | |
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| 0.1557 | 0.4146 | 4500 | 0.1485 | |
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| 0.1536 | 0.4607 | 5000 | 0.1441 | |
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| 0.1344 | 0.5067 | 5500 | 0.1399 | |
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| 0.1195 | 0.5528 | 6000 | 0.1355 | |
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| 0.1209 | 0.5989 | 6500 | 0.1316 | |
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| 0.137 | 0.6450 | 7000 | 0.1284 | |
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| 0.117 | 0.6910 | 7500 | 0.1253 | |
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| 0.116 | 0.7371 | 8000 | 0.1228 | |
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| 0.1259 | 0.7832 | 8500 | 0.1206 | |
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| 0.1147 | 0.8292 | 9000 | 0.1187 | |
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| 0.1175 | 0.8753 | 9500 | 0.1175 | |
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| 0.1117 | 0.9214 | 10000 | 0.1168 | |
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| 0.1133 | 0.9674 | 10500 | 0.1166 | |
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### Framework versions |
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- Transformers 4.45.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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