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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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datasets: |
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- hdfs_rlhf_log_summary_dataset |
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metrics: |
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- accuracy |
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model-index: |
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- name: log_sage_reward_model |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: hdfs_rlhf_log_summary_dataset |
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type: hdfs_rlhf_log_summary_dataset |
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config: default |
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split: None |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 1.0 |
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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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# log_sage_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 the hdfs_rlhf_log_summary_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4242 |
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- Accuracy: 1.0 |
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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: 1.41e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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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: linear |
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- num_epochs: 100 |
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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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| No log | 1.0 | 1 | 0.6936 | 0.8 | |
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| No log | 2.0 | 3 | 0.6931 | 0.8 | |
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| No log | 3.0 | 5 | 0.6928 | 1.0 | |
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| No log | 4.0 | 6 | 0.6927 | 1.0 | |
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| No log | 5.0 | 8 | 0.6923 | 1.0 | |
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| 0.2849 | 6.0 | 10 | 0.6915 | 1.0 | |
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| 0.2849 | 7.0 | 11 | 0.6908 | 1.0 | |
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| 0.2849 | 8.0 | 13 | 0.6889 | 1.0 | |
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| 0.2849 | 9.0 | 15 | 0.6838 | 1.0 | |
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| 0.2849 | 10.0 | 16 | 0.6788 | 1.0 | |
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| 0.2849 | 11.0 | 18 | 0.6633 | 1.0 | |
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| 0.2669 | 12.0 | 20 | 0.6464 | 1.0 | |
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| 0.2669 | 13.0 | 21 | 0.6422 | 1.0 | |
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| 0.2669 | 14.0 | 23 | 0.6312 | 1.0 | |
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| 0.2669 | 15.0 | 25 | 0.5991 | 1.0 | |
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| 0.2669 | 16.0 | 26 | 0.5796 | 1.0 | |
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| 0.2669 | 17.0 | 27 | 0.5571 | 1.0 | |
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| 0.2669 | 18.0 | 29 | 0.5255 | 1.0 | |
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| 0.2252 | 19.0 | 31 | 0.5055 | 1.0 | |
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| 0.2252 | 20.0 | 32 | 0.4967 | 1.0 | |
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| 0.2252 | 21.0 | 34 | 0.4841 | 1.0 | |
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| 0.2252 | 22.0 | 36 | 0.4742 | 1.0 | |
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| 0.2252 | 23.0 | 37 | 0.4700 | 1.0 | |
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| 0.2252 | 24.0 | 39 | 0.4633 | 1.0 | |
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| 0.1245 | 25.0 | 41 | 0.4573 | 1.0 | |
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| 0.1245 | 26.0 | 42 | 0.4547 | 1.0 | |
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| 0.1245 | 27.0 | 44 | 0.4501 | 1.0 | |
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| 0.1245 | 28.0 | 46 | 0.4462 | 1.0 | |
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| 0.1245 | 29.0 | 47 | 0.4444 | 1.0 | |
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| 0.1245 | 30.0 | 49 | 0.4415 | 1.0 | |
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| 0.0996 | 31.0 | 51 | 0.4390 | 1.0 | |
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| 0.0996 | 32.0 | 52 | 0.4378 | 1.0 | |
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| 0.0996 | 33.0 | 53 | 0.4368 | 1.0 | |
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| 0.0996 | 34.0 | 55 | 0.4349 | 1.0 | |
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| 0.0996 | 35.0 | 57 | 0.4333 | 1.0 | |
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| 0.0996 | 36.0 | 58 | 0.4326 | 1.0 | |
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| 0.0862 | 37.0 | 60 | 0.4315 | 1.0 | |
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| 0.0862 | 38.0 | 62 | 0.4306 | 1.0 | |
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| 0.0862 | 39.0 | 63 | 0.4301 | 1.0 | |
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| 0.0862 | 40.0 | 65 | 0.4294 | 1.0 | |
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| 0.0862 | 41.0 | 67 | 0.4288 | 1.0 | |
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| 0.0862 | 42.0 | 68 | 0.4285 | 1.0 | |
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| 0.0765 | 43.0 | 70 | 0.4281 | 1.0 | |
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| 0.0765 | 44.0 | 72 | 0.4276 | 1.0 | |
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| 0.0765 | 45.0 | 73 | 0.4272 | 1.0 | |
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| 0.0765 | 46.0 | 75 | 0.4265 | 1.0 | |
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| 0.0765 | 47.0 | 77 | 0.4261 | 1.0 | |
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| 0.0765 | 48.0 | 78 | 0.4259 | 1.0 | |
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| 0.0765 | 49.0 | 79 | 0.4257 | 1.0 | |
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| 0.0783 | 50.0 | 81 | 0.4253 | 1.0 | |
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| 0.0783 | 51.0 | 83 | 0.4250 | 1.0 | |
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| 0.0783 | 52.0 | 84 | 0.4249 | 1.0 | |
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| 0.0783 | 53.0 | 86 | 0.4247 | 1.0 | |
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| 0.0783 | 54.0 | 88 | 0.4246 | 1.0 | |
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| 0.0783 | 55.0 | 89 | 0.4245 | 1.0 | |
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| 0.0652 | 56.0 | 91 | 0.4244 | 1.0 | |
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| 0.0652 | 57.0 | 93 | 0.4243 | 1.0 | |
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| 0.0652 | 58.0 | 94 | 0.4243 | 1.0 | |
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| 0.0652 | 59.0 | 96 | 0.4242 | 1.0 | |
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| 0.0652 | 60.0 | 98 | 0.4242 | 1.0 | |
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| 0.0652 | 61.0 | 99 | 0.4242 | 1.0 | |
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| 0.0655 | 61.09 | 100 | 0.4242 | 1.0 | |
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### Framework versions |
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- Transformers 4.39.0 |
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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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