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--- |
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license: apache-2.0 |
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base_model: KasuleTrevor/wav2vec2-large-xls-r-300m-lg-cv-130hr-v1 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: multilingual_speech_to_intent_wav2vec_xlsr |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# multilingual_speech_to_intent_wav2vec_xlsr |
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This model is a fine-tuned version of [KasuleTrevor/wav2vec2-large-xls-r-300m-lg-cv-130hr-v1](https://huggingface.co/KasuleTrevor/wav2vec2-large-xls-r-300m-lg-cv-130hr-v1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1493 |
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- Accuracy: 0.9804 |
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- Precision: 0.9813 |
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- Recall: 0.9804 |
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- F1: 0.9805 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.65 | 1.0 | 219 | 0.1235 | 0.9795 | 0.9799 | 0.9795 | 0.9795 | |
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| 0.2315 | 2.0 | 438 | 0.1033 | 0.9851 | 0.9854 | 0.9851 | 0.9852 | |
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| 0.2355 | 3.0 | 657 | 0.1331 | 0.9724 | 0.9740 | 0.9724 | 0.9724 | |
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| 0.1943 | 4.0 | 876 | 0.2951 | 0.9250 | 0.9304 | 0.9250 | 0.9245 | |
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| 0.1854 | 5.0 | 1095 | 0.5676 | 0.8931 | 0.9056 | 0.8931 | 0.8925 | |
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| 0.1499 | 6.0 | 1314 | 0.3552 | 0.9243 | 0.9344 | 0.9243 | 0.9240 | |
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| 0.1461 | 7.0 | 1533 | 0.2503 | 0.9441 | 0.9492 | 0.9441 | 0.9442 | |
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| 0.1407 | 8.0 | 1752 | 0.2951 | 0.9214 | 0.9269 | 0.9214 | 0.9212 | |
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| 0.116 | 9.0 | 1971 | 0.3022 | 0.9391 | 0.9425 | 0.9391 | 0.9390 | |
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| 0.1142 | 10.0 | 2190 | 0.2169 | 0.9483 | 0.9526 | 0.9483 | 0.9483 | |
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| 0.1064 | 11.0 | 2409 | 0.5370 | 0.9115 | 0.9171 | 0.9115 | 0.9111 | |
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| 0.1067 | 12.0 | 2628 | 1.1525 | 0.8259 | 0.8471 | 0.8259 | 0.8266 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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