End of training

README.md

@@ -1,20 +1,20 @@
 ---
+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-training_set_variations
   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
@@ -22,12 +22,12 @@ model-index:
       split: validation
       args: ta
     metrics:
-    - type: wer
-      value: 0.45588302699729566
-      name: Wer
-    - type: bleu
-      value: 0.30120570288375
-      name: Bleu
+    - name: Wer
+      type: wer
+      value: 1.0759957831049183
+    - name: Bleu
+      type: bleu
+      value: 0.0
 ---
 
 <!-- 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: 0.4242
-- Wer: 0.4559
-- Cer: 0.0764
-- Bleu: 0.3012
+- Loss: 6.3100
+- Wer: 1.0760
+- Cer: 0.7242
+- Bleu: 0.0
 
 ## Model description
 
@@ -73,21 +73,38 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    | Bleu   |
-|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
-| 13.1596       | 12.5  | 50   | 6.8694          | 1.0    | 0.9625 | 0.0    |
-| 3.2131        | 25.0  | 100  | 0.4085          | 0.4707 | 0.0784 | 0.2830 |
-| 0.1719        | 37.5  | 150  | 0.2583          | 0.3920 | 0.0650 | 0.3818 |
-| 0.0962        | 50.0  | 200  | 0.2869          | 0.4118 | 0.0682 | 0.3547 |
-| 0.0648        | 62.5  | 250  | 0.3209          | 0.4213 | 0.0696 | 0.3435 |
-| 0.0613        | 75.0  | 300  | 0.3404          | 0.4454 | 0.0742 | 0.3200 |
-| 0.0515        | 87.5  | 350  | 0.3744          | 0.4385 | 0.0734 | 0.3289 |
-| 0.0426        | 100.0 | 400  | 0.3835          | 0.4479 | 0.0748 | 0.3078 |
-| 0.0384        | 112.5 | 450  | 0.3776          | 0.4432 | 0.0746 | 0.3243 |
-| 0.0363        | 125.0 | 500  | 0.4053          | 0.4371 | 0.0732 | 0.3251 |
-| 0.0385        | 137.5 | 550  | 0.4225          | 0.4520 | 0.0772 | 0.3115 |
-| 0.0343        | 150.0 | 600  | 0.4295          | 0.4463 | 0.0758 | 0.3167 |
-| 0.0371        | 162.5 | 650  | 0.4242          | 0.4559 | 0.0764 | 0.3012 |
+| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    | Bleu |
+|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:----:|
+| 13.5071       | 6.25   | 50   | 7.0048          | 1.0001 | 0.9823 | 0.0  |
+| 5.6893        | 12.5   | 100  | 5.2167          | 1.0000 | 0.9089 | 0.0  |
+| 4.3569        | 18.75  | 150  | 4.3516          | 1.0125 | 0.8661 | 0.0  |
+| 3.5211        | 25.0   | 200  | 3.5506          | 1.0269 | 0.8318 | 0.0  |
+| 3.2359        | 31.25  | 250  | 3.4822          | 1.0039 | 0.8458 | 0.0  |
+| 3.1004        | 37.5   | 300  | 3.5209          | 1.0086 | 0.8185 | 0.0  |
+| 2.9953        | 43.75  | 350  | 3.5498          | 1.0121 | 0.8104 | 0.0  |
+| 2.779         | 50.0   | 400  | 3.6218          | 1.0170 | 0.7777 | 0.0  |
+| 2.6019        | 56.25  | 450  | 4.0907          | 1.0134 | 0.7504 | 0.0  |
+| 2.4589        | 62.5   | 500  | 3.8633          | 1.0287 | 0.7476 | 0.0  |
+| 2.2318        | 68.75  | 550  | 3.7976          | 1.0367 | 0.7239 | 0.0  |
+| 2.0073        | 75.0   | 600  | 4.0050          | 1.0234 | 0.7288 | 0.0  |
+| 1.7416        | 81.25  | 650  | 4.2022          | 1.0126 | 0.7231 | 0.0  |
+| 1.5467        | 87.5   | 700  | 4.4087          | 1.0469 | 0.7197 | 0.0  |
+| 1.3716        | 93.75  | 750  | 4.5391          | 1.0471 | 0.7185 | 0.0  |
+| 1.2237        | 100.0  | 800  | 4.8405          | 1.0398 | 0.7152 | 0.0  |
+| 1.1216        | 106.25 | 850  | 5.0209          | 1.0421 | 0.7160 | 0.0  |
+| 1.0274        | 112.5  | 900  | 5.0349          | 1.0669 | 0.7160 | 0.0  |
+| 0.9325        | 118.75 | 950  | 5.2384          | 1.0500 | 0.7198 | 0.0  |
+| 0.8486        | 125.0  | 1000 | 5.3843          | 1.0614 | 0.7131 | 0.0  |
+| 0.7996        | 131.25 | 1050 | 5.4558          | 1.0622 | 0.7181 | 0.0  |
+| 0.7479        | 137.5  | 1100 | 5.6746          | 1.0622 | 0.7205 | 0.0  |
+| 0.6972        | 143.75 | 1150 | 5.7069          | 1.1182 | 0.7218 | 0.0  |
+| 0.6596        | 150.0  | 1200 | 5.7678          | 1.0883 | 0.7221 | 0.0  |
+| 0.6213        | 156.25 | 1250 | 5.9645          | 1.0700 | 0.7191 | 0.0  |
+| 0.5905        | 162.5  | 1300 | 6.0098          | 1.0970 | 0.7210 | 0.0  |
+| 0.5532        | 168.75 | 1350 | 6.0379          | 1.0981 | 0.7235 | 0.0  |
+| 0.5336        | 175.0  | 1400 | 6.2079          | 1.0564 | 0.7210 | 0.0  |
+| 0.4955        | 181.25 | 1450 | 6.1618          | 1.0717 | 0.7225 | 0.0  |
+| 0.4851        | 187.5  | 1500 | 6.3100          | 1.0760 | 0.7242 | 0.0  |
 
 
 ### Framework versions

adapter.tam-256.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b003b0d7962f0863c6a5d7cdb03e94664beef147a6ff472a5d16bbc67c314604
+size 8926640

model.safetensors

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 version https://git-lfs.github.com/spec/v1
-oid sha256:44f9e460a1e83b694d2f89ef4eaa463ba2483adc1fbd8eb63c39035095930725
+oid sha256:484b3f03bb3ea507d1a1d9fce95ef7a6ea8c4f23b9669b6eb005542c6d29e163
 size 3859019024