End of training
Browse files- README.md +81 -196
- config.json +117 -0
- model.safetensors +3 -0
- preprocessor_config.json +9 -0
- runs/Jun17_18-04-12_9bd4b6e1a98e/events.out.tfevents.1718647507.9bd4b6e1a98e.2514.0 +3 -0
- training_args.bin +3 -0
README.md
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###
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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[More Information Needed]
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## Evaluation
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### Testing Data, Factors & Metrics
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#### Testing Data
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#### Factors
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#### Metrics
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### Results
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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**APA:**
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## Glossary [optional]
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## More Information [optional]
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## Model Card Authors [optional]
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## Model Card Contact
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[More Information Needed]
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-large-xlsr-53
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: wav2vec_new
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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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# wav2vec_new
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2743
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- Wer: 0.1376
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- Cer: 0.1333
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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: 16
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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: 32
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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: 20
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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 | Wer | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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| 32.6273 | 1.0 | 26 | 32.5059 | 0.9394 | 0.7539 |
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| 27.4795 | 2.0 | 52 | 22.9788 | 0.9996 | 0.9996 |
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| 16.8834 | 3.0 | 78 | 7.6200 | 1.0 | 1.0 |
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| 6.2939 | 4.0 | 104 | 4.0929 | 1.0 | 1.0 |
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| 3.5881 | 5.0 | 130 | 3.4107 | 1.0 | 1.0 |
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| 3.3449 | 6.0 | 156 | 3.2649 | 1.0 | 1.0 |
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| 3.2703 | 7.0 | 182 | 3.2285 | 1.0 | 1.0 |
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| 3.253 | 8.0 | 208 | 3.2188 | 1.0 | 1.0 |
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| 3.2074 | 9.0 | 234 | 3.1777 | 1.0 | 1.0 |
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| 3.2992 | 10.0 | 260 | 3.1773 | 1.0 | 1.0 |
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| 3.2007 | 11.0 | 286 | 3.1827 | 1.0 | 1.0 |
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| 3.1878 | 12.0 | 312 | 3.1493 | 1.0 | 1.0 |
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| 3.1495 | 13.0 | 338 | 3.0784 | 1.0 | 1.0 |
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| 3.082 | 14.0 | 364 | 2.9135 | 1.0 | 1.0 |
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| 2.8619 | 15.0 | 390 | 2.7388 | 1.0 | 1.0 |
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| 2.6435 | 16.0 | 416 | 2.4690 | 0.8928 | 0.9056 |
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| 2.0885 | 17.0 | 442 | 1.7109 | 0.8447 | 0.8546 |
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| 1.622 | 18.0 | 468 | 1.0533 | 0.4430 | 0.4414 |
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| 0.8878 | 19.0 | 494 | 0.5311 | 0.2669 | 0.2651 |
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| 0.4516 | 20.0 | 520 | 0.2743 | 0.1376 | 0.1333 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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config.json
ADDED
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{
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"_name_or_path": "facebook/wav2vec2-large-xlsr-53",
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"activation_dropout": 0.0,
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"adapter_attn_dim": null,
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"adapter_kernel_size": 3,
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"adapter_stride": 2,
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"add_adapter": false,
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"apply_spec_augment": true,
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"architectures": [
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"Wav2Vec2ForCTC"
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],
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"attention_dropout": 0.1,
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"bos_token_id": 1,
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"classifier_proj_size": 256,
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"codevector_dim": 768,
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"contrastive_logits_temperature": 0.1,
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"conv_bias": true,
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"conv_dim": [
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512,
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512,
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512,
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512,
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512,
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512,
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512
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],
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"conv_kernel": [
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10,
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2,
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],
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"conv_stride": [
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5,
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2,
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],
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"ctc_loss_reduction": "mean",
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"ctc_zero_infinity": false,
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"diversity_loss_weight": 0.1,
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"do_stable_layer_norm": true,
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"eos_token_id": 2,
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"feat_extract_activation": "gelu",
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"feat_extract_dropout": 0.0,
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"feat_extract_norm": "layer",
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"feat_proj_dropout": 0.0,
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"feat_quantizer_dropout": 0.0,
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"final_dropout": 0.0,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.1,
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"mask_channel_length": 10,
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"mask_channel_min_space": 1,
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"mask_channel_other": 0.0,
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"mask_channel_prob": 0.0,
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"mask_channel_selection": "static",
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_min_space": 1,
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"mask_time_other": 0.0,
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"mask_time_prob": 0.05,
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"mask_time_selection": "static",
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"model_type": "wav2vec2",
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"num_adapter_layers": 3,
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"num_attention_heads": 16,
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"num_codevector_groups": 2,
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"num_codevectors_per_group": 320,
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"num_conv_pos_embedding_groups": 16,
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"num_conv_pos_embeddings": 128,
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"num_feat_extract_layers": 7,
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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": 37,
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"proj_codevector_dim": 768,
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"tdnn_dilation": [
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1,
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1,
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1
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],
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98 |
+
"tdnn_dim": [
|
99 |
+
512,
|
100 |
+
512,
|
101 |
+
512,
|
102 |
+
512,
|
103 |
+
1500
|
104 |
+
],
|
105 |
+
"tdnn_kernel": [
|
106 |
+
5,
|
107 |
+
3,
|
108 |
+
3,
|
109 |
+
1,
|
110 |
+
1
|
111 |
+
],
|
112 |
+
"torch_dtype": "float32",
|
113 |
+
"transformers_version": "4.41.2",
|
114 |
+
"use_weighted_layer_sum": false,
|
115 |
+
"vocab_size": 40,
|
116 |
+
"xvector_output_dim": 512
|
117 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:fe67f52007bc4751534ffb86544d1df097307b0a62fc550dedb86a4f2f3e77b7
|
3 |
+
size 1261971480
|
preprocessor_config.json
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"do_normalize": true,
|
3 |
+
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
|
4 |
+
"feature_size": 1,
|
5 |
+
"padding_side": "right",
|
6 |
+
"padding_value": 0,
|
7 |
+
"return_attention_mask": true,
|
8 |
+
"sampling_rate": 16000
|
9 |
+
}
|
runs/Jun17_18-04-12_9bd4b6e1a98e/events.out.tfevents.1718647507.9bd4b6e1a98e.2514.0
ADDED
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
1 |
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version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:1e1bde3837ba5eecf6ccd75f39e6832315e20f76f6a2e575e7e1955513089e6e
|
3 |
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size 25041
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f8b31963a5334321441ab99b1749b3369c485f5c3fabef2e530125d91e77ff82
|
3 |
+
size 5112
|