update model card README.md

README.md

@@ -12,10 +12,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # wav2vec2-base-timit-demo-colab-1
 
-This model is a fine-tuned version of [zasheza/wav2vec2-base-timit-demo-colab-1](https://huggingface.co/zasheza/wav2vec2-base-timit-demo-colab-1) on the None dataset.
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8811
-- Wer: 0.4169
+- Loss: 0.9634
+- Wer: 0.4398
 
 ## Model description
 
@@ -34,27 +34,29 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
+- learning_rate: 0.0002
 - train_batch_size: 6
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 800
-- num_epochs: 40
+- num_epochs: 50
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.161         | 5.26  | 500  | 0.7465          | 0.4496 |
-| 0.1852        | 10.53 | 1000 | 0.8108          | 0.4739 |
-| 0.1457        | 15.79 | 1500 | 0.9073          | 0.4600 |
-| 0.1073        | 21.05 | 2000 | 0.8817          | 0.4486 |
-| 0.085         | 26.32 | 2500 | 0.9262          | 0.4442 |
-| 0.0753        | 31.58 | 3000 | 0.8838          | 0.4337 |
-| 0.0647        | 36.84 | 3500 | 0.8811          | 0.4169 |
+| 4.8991        | 5.26  | 500  | 1.4319          | 0.7522 |
+| 0.8555        | 10.53 | 1000 | 0.7895          | 0.5818 |
+| 0.4584        | 15.79 | 1500 | 0.7198          | 0.5211 |
+| 0.3096        | 21.05 | 2000 | 0.7983          | 0.5118 |
+| 0.2165        | 26.32 | 2500 | 0.7893          | 0.4745 |
+| 0.163         | 31.58 | 3000 | 0.8779          | 0.4589 |
+| 0.1144        | 36.84 | 3500 | 0.9256          | 0.4540 |
+| 0.0886        | 42.11 | 4000 | 0.9184          | 0.4530 |
+| 0.0668        | 47.37 | 4500 | 0.9634          | 0.4398 |
 
 
 ### Framework versions