LambdaX-AI/SeqClsBertFullDataset

README.md

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+---
+license: cc-by-sa-4.0
+base_model: nlpaueb/bert-base-uncased-contracts
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: output
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# output
+
+This model is a fine-tuned version of [nlpaueb/bert-base-uncased-contracts](https://huggingface.co/nlpaueb/bert-base-uncased-contracts) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6712
+- Accuracy: 0.8288
+- Precision: 0.8218
+- Recall: 0.8288
+- F1: 0.8182
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6899        | 1.0   | 2036  | 0.6712          | 0.8288   | 0.8218    | 0.8288 | 0.8182 |
+| 0.4942        | 2.0   | 4072  | 0.7382          | 0.8306   | 0.8386    | 0.8306 | 0.8265 |
+| 0.3387        | 3.0   | 6108  | 0.7275          | 0.8487   | 0.8568    | 0.8487 | 0.8473 |
+| 0.1892        | 4.0   | 8144  | 0.7668          | 0.8642   | 0.8626    | 0.8642 | 0.8600 |
+| 0.125         | 5.0   | 10180 | 0.8604          | 0.8583   | 0.8581    | 0.8583 | 0.8556 |
+| 0.0673        | 6.0   | 12216 | 0.8526          | 0.8649   | 0.8651    | 0.8649 | 0.8629 |
+| 0.0237        | 7.0   | 14252 | 0.8789          | 0.8657   | 0.8660    | 0.8657 | 0.8649 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Tokenizers 0.15.0

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