End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+datasets:
+- RobZamp/sick
+metrics:
+- accuracy
+model-index:
+- name: bert-base-cased-fp-sick
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: sick
+      type: RobZamp/sick
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8545454545454545
+---
+
+<!-- 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. -->
+
+# bert-base-cased-fp-sick
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the sick dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3973
+- Accuracy: 0.8545
+
+## 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: 2e-05
+- train_batch_size: 64
+- eval_batch_size: 32
+- seed: 34
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 70   | 0.6825          | 0.6727   |
+| No log        | 2.0   | 140  | 0.4141          | 0.8505   |
+| No log        | 3.0   | 210  | 0.3973          | 0.8545   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0