DarshanDeshpande commited on
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distilbert_eli5_reward_model

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README.md ADDED
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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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+ - generated_from_trainer
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+ model-index:
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+ - name: distilbert_eli5_reward_model
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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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+ # distilbert_eli5_reward_model
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+
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6934
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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: 0.005
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+ - train_batch_size: 256
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+ - eval_batch_size: 256
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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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: cosine
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+ - lr_scheduler_warmup_steps: 10
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.6932 | 1.28 | 100 | 0.6913 |
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+ | 0.6933 | 2.56 | 200 | 0.6934 |
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+
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+
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+ ### Framework versions
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+
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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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+ "initializer_range": 0.02,
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+ "model_type": "distilbert",
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+ "n_heads": 12,
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+ "n_layers": 6,
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+ "pad_token_id": 0,
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+ "problem_type": "single_label_classification",
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+ "qa_dropout": 0.1,
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+ "seq_classif_dropout": 0.2,
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+ "tie_weights_": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.2",
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+ "vocab_size": 30522
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+ }
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