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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-demo
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-xlsr-demo
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on ASCEND (a Mandarin-English codeswitching dataset).
It achieves the following results on the evaluation set:
- Loss: 1.6751
- Wer: 0.7846
## 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: 8
- 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 10.5108 | 0.5701 | 500 | 15.4314 | 1.0 |
| 5.61 | 1.1403 | 1000 | 11.3143 | 1.0 |
| 5.546 | 1.7104 | 1500 | 9.6388 | 1.0 |
| 5.1105 | 2.2805 | 2000 | 5.9376 | 1.0 |
| 4.9007 | 2.8506 | 2500 | 5.7582 | 1.0 |
| 4.5876 | 3.4208 | 3000 | 6.7190 | 1.0 |
| 4.3145 | 3.9909 | 3500 | 4.6527 | 1.0 |
| 3.5332 | 4.5610 | 4000 | 3.3622 | 1.0011 |
| 2.9071 | 5.1311 | 4500 | 2.7400 | 1.0176 |
| 2.5077 | 5.7013 | 5000 | 2.8219 | 0.9460 |
| 2.4145 | 6.2714 | 5500 | 2.4336 | 0.9570 |
| 2.2432 | 6.8415 | 6000 | 2.1500 | 0.9169 |
| 2.1376 | 7.4116 | 6500 | 2.1445 | 0.8930 |
| 2.0841 | 7.9818 | 7000 | 2.1312 | 0.8864 |
| 1.8288 | 8.5519 | 7500 | 1.9040 | 0.8728 |
| 1.6863 | 9.1220 | 8000 | 1.8913 | 0.8434 |
| 1.7453 | 9.6921 | 8500 | 2.1214 | 0.8507 |
| 1.6896 | 10.2623 | 9000 | 1.8329 | 0.8548 |
| 1.6063 | 10.8324 | 9500 | 1.8248 | 0.8386 |
| 1.3838 | 11.4025 | 10000 | 1.7811 | 0.8379 |
| 1.5255 | 11.9726 | 10500 | 2.3148 | 0.8390 |
| 1.4269 | 12.5428 | 11000 | 2.1530 | 0.8184 |
| 1.3452 | 13.1129 | 11500 | 1.7208 | 0.8221 |
| 1.35 | 13.6830 | 12000 | 1.8269 | 0.8290 |
| 1.3656 | 14.2531 | 12500 | 1.6902 | 0.8313 |
| 1.2036 | 14.8233 | 13000 | 2.0816 | 0.8206 |
| 1.2144 | 15.3934 | 13500 | 1.7623 | 0.8103 |
| 1.1648 | 15.9635 | 14000 | 1.7197 | 0.8154 |
| 1.1341 | 16.5336 | 14500 | 1.7560 | 0.8110 |
| 1.0716 | 17.1038 | 15000 | 1.7750 | 0.8099 |
| 1.1187 | 17.6739 | 15500 | 1.7946 | 0.8180 |
| 1.0633 | 18.2440 | 16000 | 1.7877 | 0.7996 |
| 1.0069 | 18.8141 | 16500 | 1.8482 | 0.8243 |
| 0.9703 | 19.3843 | 17000 | 1.6073 | 0.7960 |
| 1.0122 | 19.9544 | 17500 | 1.7191 | 0.8099 |
| 0.9993 | 20.5245 | 18000 | 1.7208 | 0.7956 |
| 0.9861 | 21.0946 | 18500 | 1.6628 | 0.7949 |
| 0.9621 | 21.6648 | 19000 | 1.7685 | 0.7930 |
| 0.8936 | 22.2349 | 19500 | 1.7232 | 0.8026 |
| 0.888 | 22.8050 | 20000 | 1.7204 | 0.8015 |
| 0.9027 | 23.3751 | 20500 | 1.7844 | 0.7923 |
| 0.8808 | 23.9453 | 21000 | 1.7159 | 0.7945 |
| 0.8652 | 24.5154 | 21500 | 1.6887 | 0.7934 |
| 0.7545 | 25.0855 | 22000 | 1.6633 | 0.7937 |
| 0.7664 | 25.6556 | 22500 | 1.6745 | 0.7919 |
| 0.7518 | 26.2258 | 23000 | 1.7122 | 0.7930 |
| 0.8475 | 26.7959 | 23500 | 1.6901 | 0.7868 |
| 0.7527 | 27.3660 | 24000 | 1.6937 | 0.7835 |
| 0.7531 | 27.9361 | 24500 | 1.6835 | 0.7820 |
| 0.7686 | 28.5063 | 25000 | 1.6734 | 0.7901 |
| 0.7525 | 29.0764 | 25500 | 1.6766 | 0.7868 |
| 0.7765 | 29.6465 | 26000 | 1.6751 | 0.7846 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0
- Datasets 2.19.2
- Tokenizers 0.19.1
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