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torgo_xlsr_finetune_M05
macarious/torgo_xlsr_finetune_M05
torgo_xlsr_finetune_M05 is a automatic speech recognition model from macarious. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 6, 2024
- Updated
- Mar 6, 2024
- SHA
- 5d5ac858
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. -->
torgo_xlsr_finetune_M05
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2781
- Wer: 0.2436
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.5164 | 0.84 | 1000 | 3.3225 | 1.0 |
| 1.535 | 1.68 | 2000 | 1.5429 | 0.7317 |
| 0.8257 | 2.53 | 3000 | 1.3691 | 0.5730 |
| 0.6012 | 3.37 | 4000 | 1.2522 | 0.4660 |
| 0.491 | 4.21 | 5000 | 1.1413 | 0.4295 |
| 0.4401 | 5.05 | 6000 | 1.4117 | 0.3744 |
| 0.3768 | 5.89 | 7000 | 1.3632 | 0.3531 |
| 0.3746 | 6.73 | 8000 | 1.4208 | 0.3557 |
| 0.3127 | 7.58 | 9000 | 1.3584 | 0.3336 |
| 0.2595 | 8.42 | 10000 | 0.9971 | 0.2878 |
| 0.2458 | 9.26 | 11000 | 1.2794 | 0.3166 |
| 0.2638 | 10.1 | 12000 | 1.1851 | 0.2861 |
| 0.2384 | 10.94 | 13000 | 1.2144 | 0.2810 |
| 0.215 | 11.78 | 14000 | 1.1125 | 0.2623 |
| 0.2095 | 12.63 | 15000 | 1.5495 | 0.3081 |
| 0.1939 | 13.47 | 16000 | 1.4090 | 0.2818 |
| 0.1757 | 14.31 | 17000 | 1.3261 | 0.2564 |
| 0.1629 | 15.15 | 18000 | 1.3435 | 0.2453 |
| 0.152 | 15.99 | 19000 | 1.3273 | 0.2479 |
| 0.1516 | 16.84 | 20000 | 1.2215 | 0.2292 |
| 0.155 | 17.68 | 21000 | 1.3536 | 0.2453 |
| 0.135 | 18.52 | 22000 | 1.3292 | 0.2470 |
| 0.1206 | 19.36 | 23000 | 1.2781 | 0.2436 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Mar 6, 2024
- Updated
- Mar 6, 2024