End of training

README.md

@@ -4,9 +4,24 @@ tags:
 - generated_from_trainer
 datasets:
 - common_voice_16_0
+metrics:
+- wer
 model-index:
 - name: w2v-bert-2.0-ur
-  results: []
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_16_0
+      type: common_voice_16_0
+      config: ur
+      split: test
+      args: ur
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.2984838198687486
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,6 +30,9 @@ should probably proofread and complete it, then remove this comment. -->
 # w2v-bert-2.0-ur
 
 This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the common_voice_16_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: inf
+- Wer: 0.2985
 
 ## Model description
 
@@ -42,9 +60,19 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- num_epochs: 3
+- num_epochs: 10
 - mixed_precision_training: Native AMP
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.2789        | 2.4   | 300  | inf             | 0.3200 |
+| 0.2724        | 4.8   | 600  | inf             | 0.3320 |
+| 0.1912        | 7.2   | 900  | inf             | 0.2935 |
+| 0.0931        | 9.6   | 1200 | inf             | 0.2985 |
+
+
 ### Framework versions
 
 - Transformers 4.37.0.dev0

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