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README.md
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---
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license: cc-by-nc-4.0
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base_model: facebook/mms-1b-fl102
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_6_1
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metrics:
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- wer
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model-index:
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- name: wav2vec2-large-mms-1b-hindi-colab
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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_6_1
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type: common_voice_6_1
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config: hi
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split: test
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args: hi
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metrics:
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- name: Wer
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type: wer
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value: 0.32018561484918795
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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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# wav2vec2-large-mms-1b-hindi-colab
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This model is a fine-tuned version of [facebook/mms-1b-fl102](https://huggingface.co/facebook/mms-1b-fl102) on the common_voice_6_1 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3535
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- Wer: 0.3202
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.001
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 10
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 16.7585 | 0.14 | 10 | 10.2106 | 2.0951 |
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| 6.9602 | 0.27 | 20 | 3.7700 | 1.0046 |
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| 2.4653 | 0.41 | 30 | 1.3321 | 0.6763 |
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| 1.0919 | 0.55 | 40 | 0.6594 | 0.4664 |
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| 0.7645 | 0.68 | 50 | 0.4930 | 0.3910 |
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| 0.8434 | 0.82 | 60 | 0.4819 | 0.3898 |
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| 0.5118 | 0.96 | 70 | 0.4492 | 0.3817 |
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| 0.6097 | 1.1 | 80 | 0.4299 | 0.4327 |
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| 0.4698 | 1.23 | 90 | 0.4308 | 0.3643 |
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| 0.5402 | 1.37 | 100 | 0.4042 | 0.4107 |
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| 0.5622 | 1.51 | 110 | 0.4156 | 0.3701 |
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| 0.4084 | 1.64 | 120 | 0.4138 | 0.3701 |
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| 0.4888 | 1.78 | 130 | 0.3917 | 0.3434 |
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| 0.4253 | 1.92 | 140 | 0.3852 | 0.3457 |
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| 0.5004 | 2.05 | 150 | 0.3843 | 0.3364 |
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| 0.3791 | 2.19 | 160 | 0.3841 | 0.3469 |
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| 0.3302 | 2.33 | 170 | 0.3764 | 0.3271 |
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| 0.4047 | 2.47 | 180 | 0.3689 | 0.3364 |
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| 0.2951 | 2.6 | 190 | 0.3657 | 0.3329 |
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| 0.3545 | 2.74 | 200 | 0.3582 | 0.3306 |
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| 0.3736 | 2.88 | 210 | 0.3585 | 0.3248 |
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| 0.388 | 3.01 | 220 | 0.3602 | 0.3237 |
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| 0.2997 | 3.15 | 230 | 0.3624 | 0.3167 |
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| 0.3704 | 3.29 | 240 | 0.3625 | 0.3190 |
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| 0.2095 | 3.42 | 250 | 0.3571 | 0.3248 |
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| 0.3564 | 3.56 | 260 | 0.3570 | 0.3202 |
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| 0.2119 | 3.7 | 270 | 0.3550 | 0.3225 |
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| 0.3697 | 3.84 | 280 | 0.3542 | 0.3190 |
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| 0.3551 | 3.97 | 290 | 0.3535 | 0.3202 |
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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