Training in progress, step 23000

.ipynb_checkpoints/README-checkpoint.md

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+---
+language:
+- ca
+license: apache-2.0
+tags:
+- automatic-speech-recognition
+- mozilla-foundation/common_voice_8_0
+- collectivat/tv3_parla
+- projecte-aina/parlament_parla
+- generated_from_trainer
+- robust-speech-event
+datasets:
+- mozilla-foundation/common_voice_8_0
+- collectivat/tv3_parla
+- projecte-aina/parlament_parla
+model-index:
+- name: wav2vec2-xls-r-300m-ca
+  results:
+  - task: 
+      name: Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: mozilla-foundation/common_voice_8_0 ca
+      type: mozilla-foundation/common_voice_8_0
+      args: ca
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 0.15636874077301
+       - name: Test CER
+         type: cer
+         value: 0.04086725403909639
+  - task: 
+      name: Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: projecte-aina/parlament_parla ca
+      type: projecte-aina/parlament_parla
+      args: clean
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 0.09940385143350199
+       - name: Test CER
+         type: cer
+         value: 0.026906712890009454
+  - task: 
+      name: Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: collectivat/tv3_parla ca
+      type: collectivat/tv3_parla
+      args: ca
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 0.27349193517342263
+       - name: Test CER
+         type: cer
+         value: 0.11571091827304163
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# wav2vec2-xls-r-300m-ca
+
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - CA dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2549
+- Wer: 0.1573
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 7.5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 2000
+- num_epochs: 12.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Wer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 6.2099        | 0.09  | 500   | 3.4125          | 1.0    |
+| 2.9961        | 0.18  | 1000  | 2.9224          | 1.0    |
+| 2.2147        | 0.26  | 1500  | 0.6521          | 0.5568 |
+| 1.3017        | 0.35  | 2000  | 0.3153          | 0.2761 |
+| 1.1196        | 0.44  | 2500  | 0.2444          | 0.2367 |
+| 1.0712        | 0.53  | 3000  | 0.2324          | 0.2132 |
+| 1.052         | 0.62  | 3500  | 0.2173          | 0.2032 |
+| 1.2813        | 2.13  | 4000  | 0.3326          | 0.2099 |
+| 1.2365        | 2.4   | 4500  | 0.3224          | 0.2003 |
+| 1.2193        | 2.66  | 5000  | 0.3198          | 0.1957 |
+| 1.2072        | 2.93  | 5500  | 0.3063          | 0.1933 |
+| 1.213         | 3.2   | 6000  | 0.3051          | 0.1980 |
+| 1.2074        | 3.46  | 6500  | 0.3012          | 0.1879 |
+| 1.1918        | 3.73  | 7000  | 0.2947          | 0.1829 |
+| 1.1893        | 4.0   | 7500  | 0.2895          | 0.1807 |
+| 1.1751        | 4.26  | 8000  | 0.2878          | 0.1776 |
+| 1.1628        | 4.53  | 8500  | 0.2835          | 0.1731 |
+| 1.1577        | 4.79  | 9000  | 0.2816          | 0.1761 |
+| 1.1448        | 5.06  | 9500  | 0.2757          | 0.1740 |
+| 1.1407        | 5.33  | 10000 | 0.2768          | 0.1798 |
+| 1.1401        | 5.59  | 10500 | 0.2780          | 0.1816 |
+| 1.1333        | 5.86  | 11000 | 0.2748          | 0.1750 |
+| 1.1571        | 6.13  | 11500 | 0.2808          | 0.1708 |
+| 1.1505        | 6.39  | 12000 | 0.2726          | 0.1692 |
+| 1.1519        | 6.66  | 12500 | 0.2749          | 0.1654 |
+| 1.136         | 6.93  | 13000 | 0.2765          | 0.1643 |
+| 1.1326        | 7.19  | 13500 | 0.2706          | 0.1668 |
+| 1.1342        | 7.46  | 14000 | 0.2665          | 0.1638 |
+| 1.1286        | 7.72  | 14500 | 0.2669          | 0.1636 |
+| 1.1243        | 7.99  | 15000 | 0.2619          | 0.1623 |
+| 1.1173        | 8.26  | 15500 | 0.2652          | 0.1604 |
+| 1.1129        | 8.52  | 16000 | 0.2610          | 0.1598 |
+| 1.1091        | 8.79  | 16500 | 0.2608          | 0.1584 |
+| 1.1053        | 9.06  | 17000 | 0.2633          | 0.1664 |
+| 1.1004        | 9.32  | 17500 | 0.2594          | 0.1662 |
+| 1.0995        | 9.59  | 18000 | 0.2623          | 0.1569 |
+| 1.0964        | 9.86  | 18500 | 0.2624          | 0.1597 |
+| 1.09          | 10.12 | 19000 | 0.2577          | 0.1578 |
+| 1.089         | 10.39 | 19500 | 0.2574          | 0.1531 |
+| 1.0864        | 10.66 | 20000 | 0.2556          | 0.1546 |
+| 1.0806        | 10.92 | 20500 | 0.2548          | 0.1583 |
+| 1.0842        | 11.19 | 21000 | 0.2550          | 0.1542 |
+| 1.0805        | 11.45 | 21500 | 0.2561          | 0.1524 |
+| 1.0722        | 11.72 | 22000 | 0.2540          | 0.1566 |
+| 1.0763        | 11.99 | 22500 | 0.2549          | 0.1572 |
+
+
+### Framework versions
+
+- Transformers 4.16.0.dev0
+- Pytorch 1.10.1+cu102
+- Datasets 1.18.1
+- Tokenizers 0.11.0

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