File size: 2,687 Bytes
551a4b6 |
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 |
---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-nsc-demo-4
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-base-nsc-demo-4
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3016
- Wer: 0.1720
## 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: 5.9591386586384804e-05
- train_batch_size: 32
- 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: 51
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7542 | 2.27 | 50 | 0.3351 | 0.1948 |
| 0.3912 | 4.55 | 100 | 0.3016 | 0.1720 |
| 0.2497 | 6.82 | 150 | 0.3247 | 0.1757 |
| 0.201 | 9.09 | 200 | 0.3111 | 0.1728 |
| 0.1602 | 11.36 | 250 | 0.3259 | 0.1723 |
| 0.1334 | 13.64 | 300 | 0.3431 | 0.1765 |
| 0.1083 | 15.91 | 350 | 0.3413 | 0.1726 |
| 0.1114 | 18.18 | 400 | 0.4089 | 0.1768 |
| 0.0828 | 20.45 | 450 | 0.3531 | 0.1765 |
| 0.0926 | 22.73 | 500 | 0.3481 | 0.1755 |
| 0.093 | 25.0 | 550 | 0.3379 | 0.1742 |
| 0.0772 | 27.27 | 600 | 0.3628 | 0.1779 |
| 0.0701 | 29.55 | 650 | 0.3747 | 0.1773 |
| 0.0736 | 31.82 | 700 | 0.3834 | 0.1808 |
| 0.0607 | 34.09 | 750 | 0.3747 | 0.1742 |
| 0.0629 | 36.36 | 800 | 0.3683 | 0.1734 |
| 0.0713 | 38.64 | 850 | 0.3671 | 0.1744 |
| 0.0728 | 40.91 | 900 | 0.3632 | 0.1749 |
| 0.0696 | 43.18 | 950 | 0.3615 | 0.1731 |
| 0.0638 | 45.45 | 1000 | 0.3591 | 0.1755 |
| 0.0552 | 47.73 | 1050 | 0.3608 | 0.1779 |
| 0.0578 | 50.0 | 1100 | 0.3630 | 0.1752 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
|