File size: 2,196 Bytes
aa74183 |
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 |
---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-nya-colab
results: []
---
<!-- 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-nya-colab
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4327
- Wer: 0.3505
## 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: 8
- 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: 100
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.1659 | 0.2 | 200 | 0.6822 | 0.5353 |
| 0.2331 | 0.39 | 400 | 0.5220 | 0.4493 |
| 0.2119 | 0.59 | 600 | 0.4967 | 0.4146 |
| 0.1995 | 0.79 | 800 | 0.5021 | 0.4025 |
| 0.1812 | 0.99 | 1000 | 0.5046 | 0.3979 |
| 0.1744 | 1.18 | 1200 | 0.4786 | 0.3884 |
| 0.1783 | 1.38 | 1400 | 0.4630 | 0.3786 |
| 0.1663 | 1.58 | 1600 | 0.4511 | 0.3634 |
| 0.1609 | 1.77 | 1800 | 0.4656 | 0.3647 |
| 0.1632 | 1.97 | 2000 | 0.4254 | 0.3553 |
| 0.1568 | 2.17 | 2200 | 0.4326 | 0.3529 |
| 0.1544 | 2.37 | 2400 | 0.4291 | 0.3477 |
| 0.1524 | 2.56 | 2600 | 0.4327 | 0.3505 |
### Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|