File size: 2,333 Bytes
19dfbde |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-ha-cv8
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-xls-r-300m-ha-cv8
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6094
- Wer: 0.5234
## 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: 16
- eval_batch_size: 8
- seed: 13
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9599 | 6.56 | 400 | 2.8650 | 1.0 |
| 2.7357 | 13.11 | 800 | 2.7377 | 0.9951 |
| 1.3012 | 19.67 | 1200 | 0.6686 | 0.7111 |
| 1.0454 | 26.23 | 1600 | 0.5686 | 0.6137 |
| 0.9069 | 32.79 | 2000 | 0.5576 | 0.5815 |
| 0.82 | 39.34 | 2400 | 0.5502 | 0.5591 |
| 0.7413 | 45.9 | 2800 | 0.5970 | 0.5586 |
| 0.6872 | 52.46 | 3200 | 0.5817 | 0.5428 |
| 0.634 | 59.02 | 3600 | 0.5636 | 0.5314 |
| 0.6022 | 65.57 | 4000 | 0.5780 | 0.5229 |
| 0.5705 | 72.13 | 4400 | 0.6036 | 0.5323 |
| 0.5408 | 78.69 | 4800 | 0.6119 | 0.5336 |
| 0.5225 | 85.25 | 5200 | 0.6105 | 0.5270 |
| 0.5265 | 91.8 | 5600 | 0.6034 | 0.5231 |
| 0.5154 | 98.36 | 6000 | 0.6094 | 0.5234 |
### Framework versions
- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0
|