File size: 2,195 Bytes
82f8fd0 5167bef 82f8fd0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 |
---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
inference: false
tags:
- generated_from_trainer
datasets:
- common_voice_15_0
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-azerbaijani-common_voice15.0
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_15_0
type: common_voice_15_0
config: az
split: test
args: az
metrics:
- name: Wer
type: wer
value: 0.2631578947368421
---
<!-- 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-large-mms-1b-azerbaijani-common_voice15.0
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_15_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3188
- Wer: 0.2632
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.6471 | 2.0 | 10 | 7.6790 | 1.0658 |
| 5.6745 | 4.0 | 20 | 4.2727 | 1.0088 |
| 3.5016 | 6.0 | 30 | 3.1003 | 1.0 |
| 2.6223 | 8.0 | 40 | 1.8137 | 1.0439 |
| 1.3939 | 10.0 | 50 | 0.6549 | 0.3947 |
| 0.3696 | 12.0 | 60 | 0.3665 | 0.2719 |
| 0.2475 | 14.0 | 70 | 0.3188 | 0.2632 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|