End of training

README.md

@@ -0,0 +1,77 @@
+---
+license: mit
+base_model: roberta-large
+tags:
+- generated_from_trainer
+datasets:
+- RobZamp/sick
+metrics:
+- accuracy
+model-index:
+- name: roberta-large-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: 0.898989898989899
+---
+
+<!-- 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. -->
+
+# roberta-large-fp-sick
+
+This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the sick dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2761
+- Accuracy: 0.8990
+
+## 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: 38
+- 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   | 0.3558          | 0.8465   |
+| No log        | 2.0   | 140  | 0.3003          | 0.8949   |
+| No log        | 3.0   | 210  | 0.2761          | 0.8990   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0