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Coolaps/TD3

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: camembert-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: result
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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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+ # result
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+
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+ This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0206
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+ - Precision: 0.0
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+ - Recall: 0.0
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+ - F1: 0.0
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+ - Accuracy: 0.9952
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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: 0.00025
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
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+ | No log | 1.0 | 25 | 0.0892 | 0.0 | 0.0 | 0.0 | 0.9818 |
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+ | No log | 2.0 | 50 | 0.0515 | 0.0 | 0.0 | 0.0 | 0.9834 |
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+ | No log | 3.0 | 75 | 0.0348 | 0.0 | 0.0 | 0.0 | 0.9921 |
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+ | No log | 4.0 | 100 | 0.0259 | 0.0 | 0.0 | 0.0 | 0.9949 |
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+ | No log | 5.0 | 125 | 0.0182 | 0.0 | 0.0 | 0.0 | 0.9956 |
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+ | No log | 6.0 | 150 | 0.0183 | 0.0 | 0.0 | 0.0 | 0.9952 |
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+ | No log | 7.0 | 175 | 0.0188 | 0.0 | 0.0 | 0.0 | 0.9952 |
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+ | No log | 8.0 | 200 | 0.0218 | 0.0 | 0.0 | 0.0 | 0.9941 |
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+ | No log | 9.0 | 225 | 0.0249 | 0.0 | 0.0 | 0.0 | 0.9941 |
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+ | No log | 10.0 | 250 | 0.0189 | 0.0 | 0.0 | 0.0 | 0.9956 |
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+ | No log | 11.0 | 275 | 0.0180 | 0.0 | 0.0 | 0.0 | 0.9952 |
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+ | No log | 12.0 | 300 | 0.0169 | 0.0 | 0.0 | 0.0 | 0.9968 |
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+ | No log | 13.0 | 325 | 0.0155 | 0.0 | 0.0 | 0.0 | 0.9968 |
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+ | No log | 14.0 | 350 | 0.0164 | 0.0 | 0.0 | 0.0 | 0.9964 |
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+ | No log | 15.0 | 375 | 0.0174 | 0.0 | 0.0 | 0.0 | 0.9949 |
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+ | No log | 16.0 | 400 | 0.0168 | 0.0 | 0.0 | 0.0 | 0.9956 |
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+ | No log | 17.0 | 425 | 0.0174 | 0.0 | 0.0 | 0.0 | 0.9960 |
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+ | No log | 18.0 | 450 | 0.0170 | 0.0 | 0.0 | 0.0 | 0.9960 |
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+ | No log | 19.0 | 475 | 0.0200 | 0.0 | 0.0 | 0.0 | 0.9949 |
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+ | 0.0231 | 20.0 | 500 | 0.0206 | 0.0 | 0.0 | 0.0 | 0.9952 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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