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STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-170

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  1. README.md +79 -0
  2. model.safetensors +1 -1
  3. runs/Apr01_05-44-46_bf7068fd9d02/events.out.tfevents.1711950291.bf7068fd9d02.3618.0 +2 -2
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: FacebookAI/roberta-base
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+ tags:
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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: STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-170
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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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+ # STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-170
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+
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+ This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.3403
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+ - Accuracy: 0.7285
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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: 3e-05
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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 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 113 | 0.7529 | 0.6816 |
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+ | No log | 2.0 | 226 | 0.7985 | 0.7097 |
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+ | No log | 3.0 | 339 | 0.8245 | 0.7097 |
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+ | No log | 4.0 | 452 | 0.8816 | 0.6798 |
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+ | 0.5011 | 5.0 | 565 | 1.0854 | 0.6929 |
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+ | 0.5011 | 6.0 | 678 | 1.1921 | 0.7135 |
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+ | 0.5011 | 7.0 | 791 | 1.3839 | 0.7228 |
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+ | 0.5011 | 8.0 | 904 | 1.4560 | 0.7247 |
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+ | 0.1649 | 9.0 | 1017 | 1.6387 | 0.7191 |
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+ | 0.1649 | 10.0 | 1130 | 1.8012 | 0.7172 |
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+ | 0.1649 | 11.0 | 1243 | 1.8790 | 0.7247 |
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+ | 0.1649 | 12.0 | 1356 | 2.0223 | 0.7116 |
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+ | 0.1649 | 13.0 | 1469 | 2.0297 | 0.7228 |
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+ | 0.0639 | 14.0 | 1582 | 2.1202 | 0.7228 |
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+ | 0.0639 | 15.0 | 1695 | 2.2489 | 0.7303 |
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+ | 0.0639 | 16.0 | 1808 | 2.2505 | 0.7266 |
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+ | 0.0639 | 17.0 | 1921 | 2.2693 | 0.7303 |
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+ | 0.0198 | 18.0 | 2034 | 2.3216 | 0.7228 |
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+ | 0.0198 | 19.0 | 2147 | 2.3244 | 0.7247 |
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+ | 0.0198 | 20.0 | 2260 | 2.3403 | 0.7285 |
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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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