End of training

README.md

@@ -24,7 +24,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 43.15937940761636
+      value: 43.723554301833566
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,8 +34,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [glob-asr/wav2vec2-large-xls-r-300m-guarani-small](https://huggingface.co/glob-asr/wav2vec2-large-xls-r-300m-guarani-small) on the Common Voice 16 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3185
-- Wer: 43.1594
+- Loss: 0.3202
+- Wer: 43.7236
 
 ## Model description
 
@@ -60,24 +60,24 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: constant_with_warmup
-- lr_scheduler_warmup_steps: 1
+- lr_scheduler_warmup_steps: 50
 - training_steps: 500
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.3978        | 1.01  | 100  | 0.3420          | 46.9111 |
-| 0.3263        | 2.02  | 200  | 0.3318          | 46.0931 |
-| 0.28          | 3.03  | 300  | 0.3226          | 44.6827 |
-| 0.2505        | 4.04  | 400  | 0.3173          | 43.9210 |
-| 0.2427        | 5.05  | 500  | 0.3185          | 43.1594 |
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.4174        | 1.0101 | 100  | 0.3535          | 47.6728 |
+| 0.3411        | 2.0202 | 200  | 0.3387          | 46.3188 |
+| 0.2905        | 3.0303 | 300  | 0.3278          | 45.7546 |
+| 0.2591        | 4.0404 | 400  | 0.3214          | 44.6544 |
+| 0.251         | 5.0505 | 500  | 0.3202          | 43.7236 |
 
 
 ### Framework versions
 
-- Transformers 4.38.2
+- Transformers 4.40.1
 - Pytorch 2.2.1+cu121
-- Datasets 2.18.0
-- Tokenizers 0.15.2
+- Datasets 2.19.0
+- Tokenizers 0.19.1