End of training

README.md

@@ -3,6 +3,11 @@ license: apache-2.0
 base_model: google/electra-base-discriminator
 tags:
 - generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
 model-index:
 - name: electra-base-multiple-choice-fp16-v2
   results: []
@@ -13,7 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # electra-base-multiple-choice-fp16-v2
 
-This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
+This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2950
+- Accuracy: 0.8960
+- Precision: 0.8927
+- Recall: 0.9003
+- F1: 0.8965
 
 ## Model description
 
@@ -41,6 +52,15 @@ The following hyperparameters were used during training:
 - num_epochs: 3
 - mixed_precision_training: Native AMP
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 269  | 0.2875          | 0.8818   | 0.8846    | 0.8782 | 0.8814 |
+| 0.3437        | 2.0   | 538  | 0.2862          | 0.8917   | 0.8912    | 0.8924 | 0.8918 |
+| 0.3437        | 3.0   | 807  | 0.2950          | 0.8960   | 0.8927    | 0.9003 | 0.8965 |
+
+
 ### Framework versions
 
 - Transformers 4.35.2

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b4a2639004d674d5bfe16c52df349dcba1748e52c74872146a9f6ed9c0edbbb2
+oid sha256:7d87970bc90aa418622ad528c00a0655958ec16160575caee59a6103a9d50405
 size 437956148