update model card README.md

README.md

@@ -4,6 +4,8 @@ tags:
 - generated_from_trainer
 datasets:
 - superb
+metrics:
+- accuracy
 model-index:
 - name: wav2vec2-base-finetuned-ks
   results: []
@@ -15,6 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
 # wav2vec2-base-finetuned-ks
 
 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0823
+- Accuracy: 0.9819
 
 ## Model description
 
@@ -34,19 +39,30 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 3e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 128
+- total_train_batch_size: 32
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 5
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3582        | 1.0   | 1596 | 0.1846          | 0.9681   |
+| 0.2013        | 2.0   | 3192 | 0.1051          | 0.9776   |
+| 0.1656        | 3.0   | 4788 | 0.0823          | 0.9819   |
+| 0.1363        | 4.0   | 6384 | 0.0801          | 0.9819   |
+| 0.0918        | 5.0   | 7980 | 0.0838          | 0.9809   |
+
+
 ### Framework versions
 
-- Transformers 4.11.3
-- Pytorch 1.12.1+cu113
-- Datasets 1.14.0
-- Tokenizers 0.10.3
+- Transformers 4.25.1
+- Pytorch 1.13.0+cu117
+- Datasets 2.7.1
+- Tokenizers 0.13.2