End of training

README.md

@@ -1,8 +1,11 @@
 ---
-license: mit
-base_model: roberta-base
 tags:
 - generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
 model-index:
 - name: roberta-base-mr-6000ar
   results: []
@@ -13,18 +16,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # roberta-base-mr-6000ar
 
-This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+This model was trained from scratch on the None dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.0844
-- eval_accuracy: 0.8987
-- eval_precision: 0.9770
-- eval_recall: 0.8333
-- eval_f1: 0.8995
-- eval_runtime: 13.1231
-- eval_samples_per_second: 28.575
-- eval_steps_per_second: 1.829
-- epoch: 3.0
-- step: 2463
+- Loss: 0.0515
+- Accuracy: 0.9413
+- Precision: 0.9643
+- Recall: 0.9265
+- F1: 0.9450
 
 ## Model description
 
@@ -49,7 +47,16 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.0185        | 1.0   | 821  | 0.0800          | 0.9173   | 0.8879    | 0.9706 | 0.9274 |
+| 0.0121        | 2.0   | 1642 | 0.0789          | 0.9147   | 0.9778    | 0.8627 | 0.9167 |
+| 0.0101        | 3.0   | 2463 | 0.0515          | 0.9413   | 0.9643    | 0.9265 | 0.9450 |
+
 
 ### Framework versions