File size: 2,974 Bytes
451d138 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-tr
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-tr
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: 0.2891
- Wer: 0.4741
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.4933 | 0.39 | 400 | 1.0543 | 0.9316 |
| 0.7039 | 0.78 | 800 | 0.6927 | 0.7702 |
| 0.4768 | 1.17 | 1200 | 0.4779 | 0.6774 |
| 0.4004 | 1.57 | 1600 | 0.4462 | 0.6450 |
| 0.3739 | 1.96 | 2000 | 0.4287 | 0.6296 |
| 0.317 | 2.35 | 2400 | 0.4395 | 0.6248 |
| 0.3027 | 2.74 | 2800 | 0.4052 | 0.6027 |
| 0.2633 | 3.13 | 3200 | 0.4026 | 0.5938 |
| 0.245 | 3.52 | 3600 | 0.3814 | 0.5902 |
| 0.2415 | 3.91 | 4000 | 0.3691 | 0.5708 |
| 0.2193 | 4.31 | 4400 | 0.3626 | 0.5623 |
| 0.2057 | 4.7 | 4800 | 0.3591 | 0.5551 |
| 0.1874 | 5.09 | 5200 | 0.3670 | 0.5512 |
| 0.1782 | 5.48 | 5600 | 0.3483 | 0.5406 |
| 0.1706 | 5.87 | 6000 | 0.3392 | 0.5338 |
| 0.153 | 6.26 | 6400 | 0.3189 | 0.5207 |
| 0.1493 | 6.65 | 6800 | 0.3185 | 0.5164 |
| 0.1381 | 7.05 | 7200 | 0.3199 | 0.5185 |
| 0.1244 | 7.44 | 7600 | 0.3082 | 0.4993 |
| 0.1182 | 7.83 | 8000 | 0.3122 | 0.4998 |
| 0.1136 | 8.22 | 8400 | 0.3003 | 0.4936 |
| 0.1047 | 8.61 | 8800 | 0.2945 | 0.4858 |
| 0.0986 | 9.0 | 9200 | 0.2827 | 0.4809 |
| 0.0925 | 9.39 | 9600 | 0.2894 | 0.4786 |
| 0.0885 | 9.78 | 10000 | 0.2891 | 0.4741 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.12.1+cu116
- Datasets 2.1.0
- Tokenizers 0.12.1
|