End of training

README.md

@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [fav-kky/wav2vec2-base-cs-80k-ClTRUS](https://huggingface.co/fav-kky/wav2vec2-base-cs-80k-ClTRUS) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 6.0118
-- Wer: 1.0817
+- Loss: 1.5716
+- Wer: 0.9831
 
 ## Model description
 
@@ -38,12 +38,12 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 4
-- eval_batch_size: 4
+- learning_rate: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - gradient_accumulation_steps: 2
-- total_train_batch_size: 8
+- 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: 0.3
@@ -54,17 +54,33 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch   | Step  | Validation Loss | Wer    |
 |:-------------:|:-------:|:-----:|:---------------:|:------:|
-| 3.1319        | 5.3333  | 2000  | 3.3683          | 1.0    |
-| 2.2224        | 10.6667 | 4000  | 2.7979          | 1.0    |
-| 1.7975        | 16.0    | 6000  | 2.8611          | 1.0054 |
-| 1.4021        | 21.3333 | 8000  | 3.2493          | 1.0107 |
-| 1.0624        | 26.6667 | 10000 | 3.8083          | 1.0402 |
-| 0.8147        | 32.0    | 12000 | 4.1691          | 1.0683 |
-| 0.6345        | 37.3333 | 14000 | 4.8640          | 1.0723 |
-| 0.5284        | 42.6667 | 16000 | 5.3956          | 1.0790 |
-| 0.4613        | 48.0    | 18000 | 5.5666          | 1.0924 |
-| 0.4049        | 53.3333 | 20000 | 5.9451          | 1.0723 |
-| 0.3765        | 58.6667 | 22000 | 6.0118          | 1.0817 |
+| 3.4027        | 2.1942  | 2000  | 3.5478          | 1.0    |
+| 3.2864        | 4.3884  | 4000  | 3.4339          | 1.0    |
+| 2.8505        | 6.5826  | 6000  | 2.8626          | 0.9998 |
+| 2.5028        | 8.7767  | 8000  | 2.5475          | 0.9989 |
+| 2.2853        | 10.9709 | 10000 | 2.3584          | 0.9989 |
+| 2.1248        | 13.1651 | 12000 | 2.2147          | 0.9992 |
+| 2.0013        | 15.3593 | 14000 | 2.1026          | 0.9989 |
+| 1.8839        | 17.5535 | 16000 | 1.9910          | 0.9986 |
+| 1.7885        | 19.7477 | 18000 | 1.9146          | 0.9991 |
+| 1.7114        | 21.9419 | 20000 | 1.8460          | 0.9977 |
+| 1.6532        | 24.1360 | 22000 | 1.7951          | 0.9968 |
+| 1.606         | 26.3302 | 24000 | 1.7419          | 0.9959 |
+| 1.5582        | 28.5244 | 26000 | 1.7155          | 0.9958 |
+| 1.5257        | 30.7186 | 28000 | 1.6877          | 0.9917 |
+| 1.4951        | 32.9128 | 30000 | 1.6671          | 0.9923 |
+| 1.4748        | 35.1070 | 32000 | 1.6511          | 0.9902 |
+| 1.4454        | 37.3012 | 34000 | 1.6320          | 0.9891 |
+| 1.4241        | 39.4953 | 36000 | 1.6238          | 0.9884 |
+| 1.4038        | 41.6895 | 38000 | 1.6056          | 0.9843 |
+| 1.3902        | 43.8837 | 40000 | 1.5955          | 0.9839 |
+| 1.3795        | 46.0779 | 42000 | 1.5908          | 0.9848 |
+| 1.3708        | 48.2721 | 44000 | 1.5855          | 0.9833 |
+| 1.3633        | 50.4663 | 46000 | 1.5863          | 0.9858 |
+| 1.3564        | 52.6604 | 48000 | 1.5791          | 0.9830 |
+| 1.3542        | 54.8546 | 50000 | 1.5714          | 0.9818 |
+| 1.3379        | 57.0488 | 52000 | 1.5722          | 0.9824 |
+| 1.3441        | 59.2430 | 54000 | 1.5716          | 0.9831 |
 
 
 ### Framework versions