End of training

README.md

@@ -25,7 +25,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 0.25254629629629627
+      value: 1.0004629629629629
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,9 +35,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the OpenSLR54 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2212
-- Wer: 0.2525
-- Cer: 0.0565
+- Loss: 10.8771
+- Wer: 1.0005
+- Cer: 0.9690
 
 ## Model description
 
@@ -60,7 +60,8 @@ The following hyperparameters were used during training:
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Use OptimizerNames.SGD and the args are:
+No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
 - num_epochs: 2
@@ -70,33 +71,22 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
 |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
-| 0.4436        | 0.0900 | 300  | 0.5638          | 0.5560 | 0.1447 |
-| 0.5495        | 0.1800 | 600  | 0.6876          | 0.6171 | 0.1641 |
-| 0.6148        | 0.2699 | 900  | 0.6872          | 0.6211 | 0.1724 |
-| 0.564         | 0.3599 | 1200 | 0.5503          | 0.5162 | 0.1326 |
-| 0.4964        | 0.4499 | 1500 | 0.5831          | 0.5319 | 0.1318 |
-| 0.4437        | 0.5399 | 1800 | 0.4913          | 0.4935 | 0.1202 |
-| 0.4441        | 0.6299 | 2100 | 0.4754          | 0.4764 | 0.1193 |
-| 0.3861        | 0.7199 | 2400 | 0.4357          | 0.4361 | 0.1055 |
-| 0.3811        | 0.8098 | 2700 | 0.4282          | 0.4137 | 0.0976 |
-| 0.3754        | 0.8998 | 3000 | 0.3905          | 0.4069 | 0.0975 |
-| 0.3511        | 0.9898 | 3300 | 0.3547          | 0.3692 | 0.0863 |
-| 0.2496        | 1.0798 | 3600 | 0.3297          | 0.3433 | 0.0796 |
-| 0.242         | 1.1698 | 3900 | 0.3125          | 0.3315 | 0.0770 |
-| 0.2378        | 1.2597 | 4200 | 0.3158          | 0.3336 | 0.0757 |
-| 0.2274        | 1.3497 | 4500 | 0.2871          | 0.3097 | 0.0722 |
-| 0.2142        | 1.4397 | 4800 | 0.3010          | 0.3058 | 0.0712 |
-| 0.1949        | 1.5297 | 5100 | 0.2767          | 0.2944 | 0.0678 |
-| 0.198         | 1.6197 | 5400 | 0.2487          | 0.2824 | 0.0639 |
-| 0.1806        | 1.7097 | 5700 | 0.2376          | 0.2674 | 0.0612 |
-| 0.1675        | 1.7996 | 6000 | 0.2293          | 0.2630 | 0.0595 |
-| 0.1671        | 1.8896 | 6300 | 0.2248          | 0.2581 | 0.0576 |
-| 0.1526        | 1.9796 | 6600 | 0.2212          | 0.2525 | 0.0565 |
+| 16.7814       | 0.1800 | 300  | 16.3800         | 1.0007 | 3.1059 |
+| 16.2838       | 0.3599 | 600  | 15.8109         | 1.0005 | 2.9213 |
+| 15.5569       | 0.5399 | 900  | 15.0093         | 1.0005 | 2.5754 |
+| 15.0336       | 0.7199 | 1200 | 14.1309         | 1.0002 | 2.0061 |
+| 13.9247       | 0.8998 | 1500 | 13.2986         | 1.0002 | 1.5023 |
+| 13.1967       | 1.0798 | 1800 | 12.5663         | 1.0002 | 1.2076 |
+| 12.4844       | 1.2597 | 2100 | 11.9662         | 1.0002 | 1.0769 |
+| 11.8394       | 1.4397 | 2400 | 11.4978         | 1.0005 | 1.0134 |
+| 11.4607       | 1.6197 | 2700 | 11.1599         | 1.0005 | 0.9855 |
+| 11.2266       | 1.7996 | 3000 | 10.9534         | 1.0005 | 0.9733 |
+| 11.0877       | 1.9796 | 3300 | 10.8771         | 1.0005 | 0.9690 |
 
 
 ### Framework versions
 
-- Transformers 4.45.0.dev0
-- Pytorch 2.4.1+cu121
-- Datasets 2.21.0
-- Tokenizers 0.19.1
+- Transformers 4.47.1
+- Pytorch 2.5.1+cxx11.abi
+- Datasets 3.2.0
+- Tokenizers 0.21.0