End of training
Browse files- README.md +61 -0
- config.json +3 -3
- pytorch_model.bin +2 -2
- training_args.bin +2 -2
README.md
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-xls-r-300m
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tags:
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- generated_from_trainer
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datasets:
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- common_voice
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model-index:
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- name: wav2vec2-large-xls-r-300m-welsh-colab
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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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# wav2vec2-large-xls-r-300m-welsh-colab
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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.
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It achieves the following results on the evaluation set:
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- eval_loss: nan
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- eval_wer: 1.0
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- eval_runtime: 400.8204
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- eval_samples_per_second: 12.025
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- eval_steps_per_second: 1.504
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- epoch: 1.07
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- step: 400
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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: 0.03
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- train_batch_size: 8
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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: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 10
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### Framework versions
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- Transformers 4.32.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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config.json
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"num_hidden_layers": 24,
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"num_negatives": 100,
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"output_hidden_size": 1024,
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"pad_token_id":
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"proj_codevector_dim": 768,
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"tdnn_dilation": [
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],
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_weighted_layer_sum": false,
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"vocab_size":
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"xvector_output_dim": 512
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}
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"num_hidden_layers": 24,
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"num_negatives": 100,
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"output_hidden_size": 1024,
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"pad_token_id": 42,
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"proj_codevector_dim": 768,
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"tdnn_dilation": [
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],
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"torch_dtype": "float32",
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"transformers_version": "4.32.0",
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"use_weighted_layer_sum": false,
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"vocab_size": 45,
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"xvector_output_dim": 512
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}
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pytorch_model.bin
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training_args.bin
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