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mms_kik
adityaydavalli/mms_kik
mms_kik is a automatic speech recognition model from adityaydavalli. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Sep 22, 2024
- Updated
- Sep 23, 2024
- SHA
- d540d71d
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
mms_kik
This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.1756
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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.4384 | 0.1576 | 100 | inf | 0.4287 |
| 0.5264 | 0.3152 | 200 | inf | 0.3938 |
| 0.4716 | 0.4728 | 300 | inf | 0.3655 |
| 0.4084 | 0.6304 | 400 | inf | 0.3319 |
| 0.3953 | 0.7880 | 500 | inf | 0.3340 |
| 0.3605 | 0.9456 | 600 | inf | 0.3109 |
| 0.3601 | 1.1032 | 700 | inf | 0.2919 |
| 0.3368 | 1.2608 | 800 | inf | 0.2746 |
| 0.3102 | 1.4184 | 900 | inf | 0.2691 |
| 0.3209 | 1.5760 | 1000 | inf | 0.2602 |
| 0.2975 | 1.7336 | 1100 | inf | 0.2488 |
| 0.2741 | 1.8913 | 1200 | inf | 0.2356 |
| 0.271 | 2.0489 | 1300 | inf | 0.2297 |
| 0.2494 | 2.2065 | 1400 | inf | 0.2233 |
| 0.254 | 2.3641 | 1500 | inf | 0.2110 |
| 0.2484 | 2.5217 | 1600 | inf | 0.2117 |
| 0.2416 | 2.6793 | 1700 | inf | 0.2020 |
| 0.2366 | 2.8369 | 1800 | inf | 0.1985 |
| 0.2313 | 2.9945 | 1900 | inf | 0.1959 |
| 0.2228 | 3.1521 | 2000 | inf | 0.1897 |
| 0.2138 | 3.3097 | 2100 | inf | 0.1868 |
| 0.2116 | 3.4673 | 2200 | inf | 0.1822 |
| 0.223 | 3.6249 | 2300 | inf | 0.1788 |
| 0.2144 | 3.7825 | 2400 | inf | 0.1774 |
| 0.2131 | 3.9401 | 2500 | inf | 0.1756 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- cc-by-nc-4.0
- Created
- Sep 22, 2024
- Updated
- Sep 23, 2024