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README.md ADDED
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+ ---
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+ license: other
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+ base_model: facebook/opt-350m
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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: my_first_reward_modeling
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+ results: []
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+ ---
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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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+
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+ # my_first_reward_modeling
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+
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+ This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6161
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+ - Accuracy: 0.6461
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 64
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 1024
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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: 1.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.7387 | 0.07 | 10 | 0.6877 | 0.5700 |
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+ | 0.6892 | 0.14 | 20 | 0.6735 | 0.5774 |
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+ | 0.6704 | 0.21 | 30 | 0.6650 | 0.5939 |
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+ | 0.6579 | 0.28 | 40 | 0.6563 | 0.6003 |
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+ | 0.6542 | 0.35 | 50 | 0.6483 | 0.6111 |
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+ | 0.6509 | 0.42 | 60 | 0.6398 | 0.6209 |
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+ | 0.64 | 0.49 | 70 | 0.6334 | 0.6301 |
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+ | 0.6322 | 0.56 | 80 | 0.6291 | 0.6354 |
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+ | 0.6268 | 0.63 | 90 | 0.6253 | 0.6397 |
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+ | 0.6254 | 0.7 | 100 | 0.6219 | 0.6401 |
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+ | 0.6213 | 0.77 | 110 | 0.6201 | 0.6436 |
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+ | 0.6284 | 0.83 | 120 | 0.6170 | 0.6454 |
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+ | 0.6233 | 0.9 | 130 | 0.6160 | 0.6452 |
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+ | 0.6192 | 0.97 | 140 | 0.6161 | 0.6461 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.2
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ "activation_function": "relu",
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+ "use_cache": true,
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+ "vocab_size": 50272,
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+ "word_embed_proj_dim": 512
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+ }
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