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@@ -1,8 +1,8 @@
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  ---
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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- base_model: facebook/wav2vec2-xls-r-300m
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  datasets:
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  - common_voice_17_0
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  metrics:
@@ -11,8 +11,8 @@ model-index:
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  - name: xls-r-300m-hbs-phoneme-unfrozen-batch16
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  results:
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  - task:
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- type: automatic-speech-recognition
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  name: Automatic Speech Recognition
 
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  dataset:
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  name: common_voice_17_0
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  type: common_voice_17_0
@@ -20,22 +20,22 @@ model-index:
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  split: test
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  args: hsb
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  metrics:
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- - type: wer
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- value: 0.4111996251171509
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- name: Wer
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/badr-nlp/xlsr-continual-finetuning/runs/7invqf4p)
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  # xls-r-300m-hbs-phoneme-unfrozen-batch16
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- This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7105
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- - Wer: 0.4112
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- - Cer: 0.0948
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  ## Model description
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@@ -70,37 +70,37 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
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- | 3.6184 | 3.2258 | 100 | 3.4215 | 1.0 | 1.0 |
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- | 3.2927 | 6.4516 | 200 | 3.2247 | 1.0 | 1.0 |
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- | 3.2291 | 9.6774 | 300 | 3.2021 | 1.0 | 1.0000 |
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- | 1.4844 | 12.9032 | 400 | 1.3507 | 0.9857 | 0.2837 |
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- | 0.4136 | 16.1290 | 500 | 0.6982 | 0.6567 | 0.1608 |
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- | 0.2346 | 19.3548 | 600 | 0.6496 | 0.5956 | 0.1466 |
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- | 0.1401 | 22.5806 | 700 | 0.6680 | 0.5565 | 0.1314 |
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- | 0.1535 | 25.8065 | 800 | 0.6597 | 0.5026 | 0.1190 |
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- | 0.1165 | 29.0323 | 900 | 0.7085 | 0.5112 | 0.1224 |
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- | 0.076 | 32.2581 | 1000 | 0.7359 | 0.5026 | 0.1195 |
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- | 0.083 | 35.4839 | 1100 | 0.7144 | 0.4991 | 0.1205 |
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- | 0.0985 | 38.7097 | 1200 | 0.6907 | 0.4756 | 0.1120 |
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- | 0.052 | 41.9355 | 1300 | 0.6806 | 0.4700 | 0.1105 |
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- | 0.0347 | 45.1613 | 1400 | 0.7097 | 0.4588 | 0.1091 |
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- | 0.0432 | 48.3871 | 1500 | 0.7086 | 0.4649 | 0.1093 |
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- | 0.0626 | 51.6129 | 1600 | 0.6947 | 0.4393 | 0.1029 |
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- | 0.0474 | 54.8387 | 1700 | 0.6915 | 0.4468 | 0.1058 |
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- | 0.057 | 58.0645 | 1800 | 0.7068 | 0.4358 | 0.1020 |
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- | 0.0373 | 61.2903 | 1900 | 0.7140 | 0.4419 | 0.1037 |
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- | 0.0994 | 64.5161 | 2000 | 0.6966 | 0.4208 | 0.0987 |
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- | 0.0503 | 67.7419 | 2100 | 0.6997 | 0.4306 | 0.0988 |
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- | 0.0418 | 70.9677 | 2200 | 0.7105 | 0.4353 | 0.1006 |
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- | 0.036 | 74.1935 | 2300 | 0.7320 | 0.4356 | 0.1024 |
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- | 0.0171 | 77.4194 | 2400 | 0.7132 | 0.4257 | 0.0994 |
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- | 0.0234 | 80.6452 | 2500 | 0.7059 | 0.4171 | 0.0967 |
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- | 0.0335 | 83.8710 | 2600 | 0.7449 | 0.4140 | 0.0973 |
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- | 0.0288 | 87.0968 | 2700 | 0.7028 | 0.4157 | 0.0964 |
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- | 0.0344 | 90.3226 | 2800 | 0.7181 | 0.4112 | 0.0960 |
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- | 0.0298 | 93.5484 | 2900 | 0.7150 | 0.4105 | 0.0951 |
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- | 0.0532 | 96.7742 | 3000 | 0.7164 | 0.4119 | 0.0950 |
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- | 0.0058 | 100.0 | 3100 | 0.7105 | 0.4112 | 0.0948 |
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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+ base_model: facebook/wav2vec2-large-xlsr-53
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  tags:
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  - generated_from_trainer
 
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  datasets:
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  - common_voice_17_0
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  metrics:
 
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  - name: xls-r-300m-hbs-phoneme-unfrozen-batch16
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  results:
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  - task:
 
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  name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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  dataset:
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  name: common_voice_17_0
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  type: common_voice_17_0
 
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  split: test
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  args: hsb
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  metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.5337394564198688
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/badr-nlp/xlsr-continual-finetuning/runs/7duhfamy)
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  # xls-r-300m-hbs-phoneme-unfrozen-batch16
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_17_0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9205
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+ - Wer: 0.5337
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+ - Cer: 0.1244
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
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+ | 4.0877 | 3.2258 | 100 | 3.7799 | 1.0 | 1.0 |
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+ | 3.2643 | 6.4516 | 200 | 3.2338 | 1.0 | 1.0 |
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+ | 3.2182 | 9.6774 | 300 | 3.1963 | 1.0 | 1.0 |
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+ | 0.8009 | 12.9032 | 400 | 0.9289 | 0.8240 | 0.2193 |
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+ | 0.2664 | 16.1290 | 500 | 0.8523 | 0.7381 | 0.1855 |
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+ | 0.1359 | 19.3548 | 600 | 0.8465 | 0.6757 | 0.1676 |
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+ | 0.1022 | 22.5806 | 700 | 0.8537 | 0.6603 | 0.1656 |
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+ | 0.0641 | 25.8065 | 800 | 0.8821 | 0.6664 | 0.1620 |
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+ | 0.0565 | 29.0323 | 900 | 0.9185 | 0.6610 | 0.1608 |
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+ | 0.068 | 32.2581 | 1000 | 0.8839 | 0.6286 | 0.1513 |
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+ | 0.0556 | 35.4839 | 1100 | 0.8898 | 0.6125 | 0.1479 |
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+ | 0.0457 | 38.7097 | 1200 | 0.8840 | 0.6204 | 0.1448 |
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+ | 0.0439 | 41.9355 | 1300 | 0.9207 | 0.6249 | 0.1490 |
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+ | 0.0296 | 45.1613 | 1400 | 0.9572 | 0.6246 | 0.1510 |
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+ | 0.0461 | 48.3871 | 1500 | 0.8875 | 0.5918 | 0.1395 |
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+ | 0.0419 | 51.6129 | 1600 | 0.8967 | 0.5846 | 0.1384 |
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+ | 0.0333 | 54.8387 | 1700 | 0.9827 | 0.5951 | 0.1420 |
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+ | 0.0318 | 58.0645 | 1800 | 0.9055 | 0.5733 | 0.1364 |
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+ | 0.0238 | 61.2903 | 1900 | 0.9497 | 0.5696 | 0.1363 |
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+ | 0.0257 | 64.5161 | 2000 | 0.9268 | 0.5590 | 0.1330 |
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+ | 0.0266 | 67.7419 | 2100 | 0.9374 | 0.5703 | 0.1351 |
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+ | 0.0292 | 70.9677 | 2200 | 0.9304 | 0.5754 | 0.1352 |
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+ | 0.0288 | 74.1935 | 2300 | 0.9419 | 0.5649 | 0.1334 |
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+ | 0.0125 | 77.4194 | 2400 | 0.9625 | 0.5581 | 0.1335 |
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+ | 0.0241 | 80.6452 | 2500 | 0.9449 | 0.5569 | 0.1313 |
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+ | 0.0217 | 83.8710 | 2600 | 0.9315 | 0.5504 | 0.1292 |
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+ | 0.0136 | 87.0968 | 2700 | 0.9079 | 0.5373 | 0.1257 |
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+ | 0.0203 | 90.3226 | 2800 | 0.8935 | 0.5373 | 0.1241 |
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+ | 0.0166 | 93.5484 | 2900 | 0.9169 | 0.5354 | 0.1239 |
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+ | 0.0114 | 96.7742 | 3000 | 0.9245 | 0.5323 | 0.1240 |
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+ | 0.011 | 100.0 | 3100 | 0.9205 | 0.5337 | 0.1244 |
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  ### Framework versions