Stuti Agarwal commited on
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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: roberta-large
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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: temp_model_outputdir
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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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+ # temp_model_outputdir
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+
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+ This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3571
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+ - Precision: 0.9390
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+ - Recall: 0.9355
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+ - F1: 0.9315
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+ - Accuracy: 0.9355
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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: 2.2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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: cosine
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+ - lr_scheduler_warmup_ratio: 0.2
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+ - num_epochs: 8
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | Precision | Recall |
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+ |:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|:---------:|:------:|
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+ | 1.9118 | 1.0 | 1511 | 0.8173 | 0.8042 | 0.7125 | 0.8320 | 0.8173 |
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+ | 0.6271 | 2.0 | 3022 | 0.8402 | 0.8360 | 0.6493 | 0.8535 | 0.8402 |
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+ | 0.5214 | 3.0 | 4533 | 0.8342 | 0.8285 | 0.7902 | 0.8391 | 0.8342 |
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+ | 0.7385 | 4.0 | 6044 | 0.8769 | 0.8724 | 0.5748 | 0.8879 | 0.8769 |
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+ | 0.6674 | 5.0 | 7555 | 0.8640 | 0.8602 | 0.5157 | 0.8802 | 0.8640 |
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+ | 0.4279 | 6.0 | 9066 | 0.9077 | 0.9029 | 0.4802 | 0.9148 | 0.9077 |
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+ | 0.5507 | 7.0 | 10577 | 0.3693 | 0.9371 | 0.9332 | 0.9288 | 0.9332 |
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+ | 0.2703 | 8.0 | 12088 | 0.3571 | 0.9390 | 0.9355 | 0.9315 | 0.9355 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.15.0
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+ "architectures": [
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