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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-uncased |
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tags: |
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- trl |
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- reward-trainer |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilbert_social_reasoning_reward_model |
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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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# distilbert_social_reasoning_reward_model |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6145 |
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- Accuracy: 0.6871 |
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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: 0.0005 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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_steps: 10 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.6733 | 0.24 | 10 | 0.6564 | 0.6725 | |
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| 0.6475 | 0.48 | 20 | 0.6191 | 0.6708 | |
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| 0.655 | 0.72 | 30 | 0.6216 | 0.6708 | |
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| 0.6489 | 0.96 | 40 | 0.6311 | 0.6708 | |
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| 0.6204 | 1.2 | 50 | 0.6837 | 0.6147 | |
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| 0.5924 | 1.44 | 60 | 0.6329 | 0.6988 | |
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| 0.6124 | 1.68 | 70 | 0.6220 | 0.6620 | |
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| 0.6123 | 1.92 | 80 | 0.6366 | 0.6515 | |
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| 0.562 | 2.16 | 90 | 0.6584 | 0.6532 | |
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| 0.5169 | 2.4 | 100 | 0.6956 | 0.6410 | |
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| 0.5045 | 2.63 | 110 | 0.6823 | 0.6392 | |
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| 0.4712 | 2.87 | 120 | 0.6927 | 0.6375 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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