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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: kids_phoneme_sm_model
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. -->
# kids_phoneme_sm_model
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5405
- Cer: 0.2770
## 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: 4e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.2595 | 0.74 | 500 | 3.7094 | 1.0 |
| 2.8393 | 1.48 | 1000 | 3.2563 | 1.0 |
| 2.7916 | 2.22 | 1500 | 3.0450 | 1.0 |
| 1.9585 | 2.96 | 2000 | 1.0280 | 0.8428 |
| 1.0099 | 3.7 | 2500 | 0.6477 | 0.5162 |
| 0.7968 | 4.44 | 3000 | 0.5551 | 0.4592 |
| 0.6977 | 5.19 | 3500 | 0.5107 | 0.4065 |
| 0.609 | 5.93 | 4000 | 0.4763 | 0.3916 |
| 0.5941 | 6.67 | 4500 | 0.4817 | 0.3850 |
| 0.5411 | 7.41 | 5000 | 0.4755 | 0.3639 |
| 0.5021 | 8.15 | 5500 | 0.4649 | 0.3622 |
| 0.4884 | 8.89 | 6000 | 0.4630 | 0.3569 |
| 0.4484 | 9.63 | 6500 | 0.4675 | 0.3420 |
| 0.4432 | 10.37 | 7000 | 0.4192 | 0.3402 |
| 0.399 | 11.11 | 7500 | 0.4508 | 0.3310 |
| 0.4215 | 11.85 | 8000 | 0.4406 | 0.3345 |
| 0.366 | 12.59 | 8500 | 0.4620 | 0.3248 |
| 0.3708 | 13.33 | 9000 | 0.4594 | 0.3327 |
| 0.3352 | 14.07 | 9500 | 0.4649 | 0.3121 |
| 0.3468 | 14.81 | 10000 | 0.4413 | 0.3020 |
| 0.3283 | 15.56 | 10500 | 0.4948 | 0.2915 |
| 0.3222 | 16.3 | 11000 | 0.4870 | 0.3025 |
| 0.3081 | 17.04 | 11500 | 0.4779 | 0.2919 |
| 0.3099 | 17.78 | 12000 | 0.4927 | 0.2871 |
| 0.2485 | 18.52 | 12500 | 0.5013 | 0.2831 |
| 0.3163 | 19.26 | 13000 | 0.4929 | 0.2888 |
| 0.2555 | 20.0 | 13500 | 0.5234 | 0.2888 |
| 0.2705 | 20.74 | 14000 | 0.5259 | 0.2818 |
| 0.2632 | 21.48 | 14500 | 0.5105 | 0.2831 |
| 0.2374 | 22.22 | 15000 | 0.5284 | 0.2845 |
| 0.2565 | 22.96 | 15500 | 0.5237 | 0.2875 |
| 0.2394 | 23.7 | 16000 | 0.5368 | 0.2818 |
| 0.2458 | 24.44 | 16500 | 0.5386 | 0.2814 |
| 0.2383 | 25.19 | 17000 | 0.5366 | 0.2788 |
| 0.2152 | 25.93 | 17500 | 0.5320 | 0.2770 |
| 0.231 | 26.67 | 18000 | 0.5441 | 0.2779 |
| 0.2061 | 27.41 | 18500 | 0.5448 | 0.2796 |
| 0.245 | 28.15 | 19000 | 0.5413 | 0.2796 |
| 0.2119 | 28.89 | 19500 | 0.5379 | 0.2774 |
| 0.2155 | 29.63 | 20000 | 0.5405 | 0.2770 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.13.0
- Tokenizers 0.13.3
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