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anhnv125
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reward-model

Text Classification
Transformers
PyTorch
Safetensors
gpt2
Generated from Trainer
text-generation-inference
Inference Endpoints
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anhnv125/reward-model

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  1. README.md +4 -24
  2. model.safetensors +1 -1
  3. pytorch_model.bin +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ChaiML/reward_models_100_170000000_cp_498032](https://huggingface.co/ChaiML/reward_models_100_170000000_cp_498032) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6275
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  ## Model description
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@@ -37,6 +37,8 @@ The following hyperparameters were used during training:
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 7
 
 
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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: 200
@@ -46,29 +48,7 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.6911 | 0.04 | 200 | 0.6674 |
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- | 0.654 | 0.09 | 400 | 0.6472 |
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- | 0.6654 | 0.13 | 600 | 0.6429 |
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- | 0.6381 | 0.17 | 800 | 0.6391 |
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- | 0.6546 | 0.21 | 1000 | 0.6381 |
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- | 0.6575 | 0.26 | 1200 | 0.6352 |
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- | 0.6458 | 0.3 | 1400 | 0.6344 |
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- | 0.6574 | 0.34 | 1600 | 0.6335 |
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- | 0.6409 | 0.39 | 1800 | 0.6314 |
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- | 0.6255 | 0.43 | 2000 | 0.6306 |
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- | 0.6342 | 0.47 | 2200 | 0.6300 |
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- | 0.6117 | 0.51 | 2400 | 0.6298 |
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- | 0.6651 | 0.56 | 2600 | 0.6307 |
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- | 0.6624 | 0.6 | 2800 | 0.6294 |
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- | 0.6213 | 0.64 | 3000 | 0.6286 |
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- | 0.6486 | 0.68 | 3200 | 0.6278 |
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- | 0.6258 | 0.73 | 3400 | 0.6277 |
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- | 0.6336 | 0.77 | 3600 | 0.6278 |
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- | 0.5842 | 0.81 | 3800 | 0.6277 |
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- | 0.6748 | 0.86 | 4000 | 0.6275 |
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- | 0.5985 | 0.9 | 4200 | 0.6275 |
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- | 0.6207 | 0.94 | 4400 | 0.6275 |
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- | 0.5901 | 0.98 | 4600 | 0.6275 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [ChaiML/reward_models_100_170000000_cp_498032](https://huggingface.co/ChaiML/reward_models_100_170000000_cp_498032) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6433
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  ## Model description
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 7
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 256
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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: 200
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.6589 | 0.68 | 200 | 0.6433 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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