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xtreme_s_xlsr_300m_mt5-small_minds14.en-US
Splend1dchan/xtreme_s_xlsr_300m_mt5-small_minds14.en-US
xtreme_s_xlsr_300m_mt5-small_minds14.en-US is a machine learning model from Splend1dchan. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- May 30, 2022
- Updated
- May 30, 2022
- SHA
- df7dcdc0
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
xtreme_s_xlsr_300m_mt5-small_minds14.en-US
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/XTREME_S - MINDS14.EN-US dataset. It achieves the following results on the evaluation set:
- Loss: 4.7321
- F1: 0.0154
- Accuracy: 0.0638
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: 8
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- 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: 100
- num_epochs: 50.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|---|---|---|---|---|---|
| 2.6067 | 3.95 | 20 | 2.6501 | 0.0112 | 0.0851 |
| 2.5614 | 7.95 | 40 | 2.8018 | 0.0133 | 0.0603 |
| 2.2836 | 11.95 | 60 | 3.0786 | 0.0084 | 0.0603 |
| 1.9597 | 15.95 | 80 | 3.2288 | 0.0126 | 0.0638 |
| 1.5566 | 19.95 | 100 | 3.6934 | 0.0178 | 0.0567 |
| 1.3168 | 23.95 | 120 | 3.9135 | 0.0150 | 0.0638 |
| 1.0598 | 27.95 | 140 | 4.2618 | 0.0084 | 0.0603 |
| 0.5721 | 31.95 | 160 | 3.7973 | 0.0354 | 0.0780 |
| 0.4402 | 35.95 | 180 | 4.6233 | 0.0179 | 0.0638 |
| 0.6113 | 39.95 | 200 | 4.6149 | 0.0208 | 0.0674 |
| 0.3938 | 43.95 | 220 | 4.7886 | 0.0159 | 0.0638 |
| 0.2473 | 47.95 | 240 | 4.7321 | 0.0154 | 0.0638 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- May 30, 2022
- Updated
- May 30, 2022