End of training

README.md

@@ -6,9 +6,24 @@ tags:
 - generated_from_trainer
 datasets:
 - common_voice_17_0
+metrics:
+- wer
 model-index:
 - name: wav2vec2-large-xls-r-300m-telugu-colab
-  results: []
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_17_0
+      type: common_voice_17_0
+      config: te
+      split: test
+      args: te
+    metrics:
+    - name: Wer
+      type: wer
+      value: 1.0
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,6 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
 # wav2vec2-large-xls-r-300m-telugu-colab
 
 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.5202
+- Wer: 1.0
 
 ## Model description
 
@@ -35,20 +53,26 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0003
-- train_batch_size: 16
+- learning_rate: 0.0001
+- train_batch_size: 4
 - eval_batch_size: 8
 - seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 32
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
-- num_epochs: 30
+- lr_scheduler_warmup_steps: 50
+- num_epochs: 50
 - mixed_precision_training: Native AMP
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Wer |
+|:-------------:|:-----:|:----:|:---------------:|:---:|
+| 3.5071        | 12.5  | 50   | 3.5170          | 1.0 |
+| 3.2841        | 25.0  | 100  | 3.5033          | 1.0 |
+| 3.0375        | 37.5  | 150  | 3.5254          | 1.0 |
+| 2.8215        | 50.0  | 200  | 3.5202          | 1.0 |
 
 
 ### Framework versions