File size: 3,050 Bytes
60f058e |
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 86 87 88 89 |
---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: kbd-asr-colab2
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. -->
# kbd-asr-colab2
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1829
- Wer: 0.3182
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.7968 | 0.1871 | 200 | 0.4521 | 0.7382 |
| 0.6536 | 0.3742 | 400 | 0.3965 | 0.7499 |
| 0.5989 | 0.5613 | 600 | 0.3850 | 0.7644 |
| 0.5212 | 0.7484 | 800 | 0.3473 | 0.6373 |
| 0.5649 | 0.9355 | 1000 | 0.2951 | 0.5633 |
| 0.4996 | 1.1225 | 1200 | 0.2771 | 0.4806 |
| 0.5247 | 1.3096 | 1400 | 0.2553 | 0.4592 |
| 0.4559 | 1.4967 | 1600 | 0.2537 | 0.4396 |
| 0.5153 | 1.6838 | 1800 | 0.2479 | 0.4364 |
| 0.4622 | 1.8709 | 2000 | 0.2363 | 0.4251 |
| 0.4533 | 2.0580 | 2200 | 0.2280 | 0.4091 |
| 0.4529 | 2.2451 | 2400 | 0.2182 | 0.4066 |
| 0.4453 | 2.4322 | 2600 | 0.2191 | 0.3902 |
| 0.4339 | 2.6193 | 2800 | 0.2135 | 0.3815 |
| 0.4179 | 2.8064 | 3000 | 0.2151 | 0.3906 |
| 0.3983 | 2.9935 | 3200 | 0.2059 | 0.3725 |
| 0.3868 | 3.1805 | 3400 | 0.2058 | 0.3614 |
| 0.3804 | 3.3676 | 3600 | 0.1959 | 0.3558 |
| 0.3934 | 3.5547 | 3800 | 0.2015 | 0.3555 |
| 0.3693 | 3.7418 | 4000 | 0.1995 | 0.3587 |
| 0.3678 | 3.9289 | 4200 | 0.2017 | 0.3876 |
| 0.4097 | 4.1160 | 4400 | 0.1893 | 0.3355 |
| 0.34 | 4.3031 | 4600 | 0.1877 | 0.3291 |
| 0.3553 | 4.4902 | 4800 | 0.1857 | 0.3222 |
| 0.3133 | 4.6773 | 5000 | 0.1839 | 0.3224 |
| 0.3077 | 4.8644 | 5200 | 0.1829 | 0.3182 |
### Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0
|