End of training

README.md

@@ -1,33 +1,33 @@
 ---
+library_name: transformers
+license: cc-by-nc-4.0
 base_model: facebook/mms-1b-all
+tags:
+- generated_from_trainer
 datasets:
 - common_voice_17_0
-library_name: transformers
-license: cc-by-nc-4.0
 metrics:
 - wer
 - bleu
-tags:
-- generated_from_trainer
 model-index:
 - name: wav2vec2-mms-1b-CV17.0
   results:
   - task:
-      type: automatic-speech-recognition
       name: Automatic Speech Recognition
+      type: automatic-speech-recognition
     dataset:
       name: common_voice_17_0
       type: common_voice_17_0
-      config: ta
-      split: test[:5%]+test[20%:25%]+test[60%:65%]+test[90%:]
-      args: ta
+      config: yo
+      split: test
+      args: yo
     metrics:
-    - type: wer
-      value: 0.39458150446496143
-      name: Wer
-    - type: bleu
-      value: 0.3894086227361947
-      name: Bleu
+    - name: Wer
+      type: wer
+      value: 0.6538388264431321
+    - name: Bleu
+      type: bleu
+      value: 0.14202013774436864
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -37,10 +37,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2560
-- Wer: 0.3946
-- Cer: 0.0667
-- Bleu: 0.3894
+- Loss: 0.6919
+- Wer: 0.6538
+- Cer: 0.2510
+- Bleu: 0.1420
 
 ## Model description
 
@@ -59,7 +59,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
+- learning_rate: 0.001
 - train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
@@ -68,23 +68,23 @@ 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_ratio: 0.15
-- training_steps: 5000
+- training_steps: 2000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    | Bleu   |
-|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|
-| 5.2362        | 0.3509 | 500  | 0.3039          | 0.4233 | 0.0716 | 0.3579 |
-| 0.2003        | 0.7018 | 1000 | 0.2726          | 0.4072 | 0.0694 | 0.3806 |
-| 0.1821        | 1.0526 | 1500 | 0.2632          | 0.3993 | 0.0677 | 0.3890 |
-| 0.1792        | 1.4035 | 2000 | 0.2602          | 0.4011 | 0.0677 | 0.3850 |
-| 0.1764        | 1.7544 | 2500 | 0.2572          | 0.3984 | 0.0674 | 0.3850 |
-| 0.1771        | 2.1053 | 3000 | 0.2570          | 0.3955 | 0.0672 | 0.3918 |
-| 0.1777        | 2.4561 | 3500 | 0.2562          | 0.3970 | 0.0670 | 0.3866 |
-| 0.1721        | 2.8070 | 4000 | 0.2547          | 0.3975 | 0.0669 | 0.3841 |
-| 0.177         | 3.1579 | 4500 | 0.2560          | 0.3949 | 0.0668 | 0.3910 |
-| 0.1765        | 3.5088 | 5000 | 0.2560          | 0.3946 | 0.0667 | 0.3894 |
+| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    | Bleu   |
+|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|
+| 6.2938        | 3.0769  | 200  | 3.8350          | 0.9981 | 0.9092 | 0.0    |
+| 2.0522        | 6.1538  | 400  | 0.7219          | 0.6997 | 0.2730 | 0.1116 |
+| 0.7043        | 9.2308  | 600  | 0.7137          | 0.7419 | 0.2682 | 0.0933 |
+| 0.6497        | 12.3077 | 800  | 0.6962          | 0.6664 | 0.2667 | 0.1318 |
+| 0.614         | 15.3846 | 1000 | 0.6680          | 0.6586 | 0.2596 | 0.1356 |
+| 0.5794        | 18.4615 | 1200 | 0.6798          | 0.6722 | 0.2599 | 0.1254 |
+| 0.5439        | 21.5385 | 1400 | 0.6724          | 0.6665 | 0.2541 | 0.1287 |
+| 0.5146        | 24.6154 | 1600 | 0.6906          | 0.6704 | 0.2513 | 0.1327 |
+| 0.489         | 27.6923 | 1800 | 0.6886          | 0.6599 | 0.2509 | 0.1390 |
+| 0.4668        | 30.7692 | 2000 | 0.6919          | 0.6538 | 0.2510 | 0.1420 |
 
 
 ### Framework versions

adapter.yor.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c5295039797811034e2a43418c20047871eaf4e450bfc8c506413bab67a58c3e
+size 8875400