End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 0.239169022417987
+      value: 0.20053544110147883
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the vivos dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3501
-- Wer: 0.2392
+- Loss: 0.3151
+- Wer: 0.2005
 
 ## Model description
 
@@ -52,15 +52,15 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 8e-05
+- learning_rate: 0.0001
 - train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
 - gradient_accumulation_steps: 4
 - total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 500
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 300
 - num_epochs: 20
 - mixed_precision_training: Native AMP
 
@@ -68,16 +68,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 8.7262        | 2.0   | 146  | 5.1186          | 1.0    |
-| 3.6815        | 4.0   | 292  | 3.6847          | 1.0    |
-| 3.4316        | 6.0   | 438  | 3.5415          | 1.0    |
-| 2.8102        | 8.0   | 584  | 1.5866          | 0.9160 |
-| 0.8818        | 10.0  | 730  | 0.5903          | 0.4066 |
-| 0.4305        | 12.0  | 876  | 0.4283          | 0.3104 |
-| 0.3067        | 14.0  | 1022 | 0.3793          | 0.2762 |
-| 0.2819        | 16.0  | 1168 | 0.3620          | 0.2496 |
-| 0.2235        | 18.0  | 1314 | 0.3507          | 0.2405 |
-| 0.211         | 20.0  | 1460 | 0.3501          | 0.2392 |
+| 7.4472        | 2.0   | 146  | 4.1025          | 1.0    |
+| 3.4729        | 4.0   | 292  | 3.6046          | 1.0    |
+| 2.8216        | 6.0   | 438  | 1.4275          | 0.8461 |
+| 0.8343        | 8.0   | 584  | 0.5637          | 0.3727 |
+| 0.4258        | 10.0  | 730  | 0.4272          | 0.2877 |
+| 0.3012        | 12.0  | 876  | 0.3548          | 0.2370 |
+| 0.2445        | 14.0  | 1022 | 0.3371          | 0.2230 |
+| 0.2328        | 16.0  | 1168 | 0.3269          | 0.2119 |
+| 0.1831        | 18.0  | 1314 | 0.3204          | 0.2058 |
+| 0.1664        | 20.0  | 1460 | 0.3151          | 0.2005 |
 
 
 ### Framework versions