jialicheng
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Commit
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Parent(s):
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Upload folder using huggingface_hub
Browse files- README.md +86 -0
- all_results.json +19 -0
- config.json +112 -0
- eval_results.json +8 -0
- model.safetensors +3 -0
- pred_logit_eval.npy +3 -0
- pred_logit_test.npy +3 -0
- pred_logit_train.npy +3 -0
- preprocessor_config.json +9 -0
- test_results.json +8 -0
- train_results.json +8 -0
- trainer_state.json +225 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: facebook/hubert-xlarge-ll60k
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tags:
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- audio-classification
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- generated_from_trainer
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datasets:
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- superb
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metrics:
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- accuracy
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model-index:
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- name: superb_ks_42
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results:
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- task:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: superb
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type: superb
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config: ks
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split: validation
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args: ks
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9872021182700794
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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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# superb_ks_42
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This model is a fine-tuned version of [facebook/hubert-xlarge-ll60k](https://huggingface.co/facebook/hubert-xlarge-ll60k) on the superb dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0579
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- Accuracy: 0.9872
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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: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 4
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- seed: 42
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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_ratio: 0.1
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 1.5639 | 1.0 | 1597 | 0.1012 | 0.9794 |
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| 0.205 | 2.0 | 3194 | 0.0720 | 0.9841 |
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| 0.1774 | 3.0 | 4791 | 0.0664 | 0.9856 |
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| 0.1549 | 4.0 | 6388 | 0.0621 | 0.9856 |
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| 0.1416 | 5.0 | 7985 | 0.0620 | 0.9859 |
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| 0.1328 | 6.0 | 9582 | 0.0614 | 0.9865 |
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| 0.1159 | 7.0 | 11179 | 0.0615 | 0.9865 |
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| 0.1211 | 8.0 | 12776 | 0.0579 | 0.9872 |
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| 0.108 | 9.0 | 14373 | 0.0566 | 0.9863 |
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| 0.1088 | 10.0 | 15970 | 0.0572 | 0.9869 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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all_results.json
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{
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"epoch": 10.0,
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"eval_accuracy": 0.9872021182700794,
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"eval_loss": 0.057863999158144,
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"eval_runtime": 34.232,
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"eval_samples_per_second": 198.586,
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"eval_steps_per_second": 0.789,
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"test_accuracy": 0.8980850373255437,
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"test_loss": 0.5234816074371338,
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"test_runtime": 16.7699,
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"test_samples_per_second": 183.722,
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"test_steps_per_second": 0.775,
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"total_flos": 4.722696547222273e+19,
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"train_accuracy": 0.9925040122127843,
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"train_loss": 0.03099818341434002,
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"train_runtime": 461.453,
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"train_samples_per_second": 110.724,
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"train_steps_per_second": 27.682
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}
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config.json
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{
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"_name_or_path": "facebook/hubert-xlarge-ll60k",
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"activation_dropout": 0.0,
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"apply_spec_augment": true,
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"architectures": [
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"HubertForSequenceClassification"
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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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"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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3,
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3,
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3,
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2,
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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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2,
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2,
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],
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"ctc_loss_reduction": "sum",
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"ctc_zero_infinity": false,
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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": 0.1,
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"feat_proj_layer_norm": true,
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"final_dropout": 0.0,
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"finetuning_task": "audio-classification",
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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": 1280,
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"id2label": {
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"0": "yes",
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"1": "no",
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"10": "_silence_",
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"11": "_unknown_",
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"2": "up",
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"3": "down",
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"4": "left",
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"5": "right",
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"6": "on",
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"7": "off",
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"8": "stop",
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"9": "go"
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},
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"initializer_range": 0.02,
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"intermediate_size": 5120,
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"label2id": {
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"_silence_": "10",
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"_unknown_": "11",
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"down": "3",
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"go": "9",
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"left": "4",
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"no": "1",
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"off": "7",
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"on": "6",
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"right": "5",
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"stop": "8",
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"up": "2",
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"yes": "0"
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},
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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": 0.075,
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"mask_time_selection": "static",
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"model_type": "hubert",
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"num_attention_heads": 16,
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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": 48,
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"pad_token_id": 0,
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"tokenizer_class": "Wav2Vec2CTCTokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.40.1",
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"use_weighted_layer_sum": false,
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"vocab_size": 32
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}
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eval_results.json
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{
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"epoch": 10.0,
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"eval_accuracy": 0.9872021182700794,
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"eval_loss": 0.057863999158144,
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"eval_runtime": 34.232,
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"eval_samples_per_second": 198.586,
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"eval_steps_per_second": 0.789
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3f2bc11bb0ef6d16449d224dc914cc834d3e8c73c64c915023349c2c379afe6b
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size 3851413640
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pred_logit_eval.npy
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version https://git-lfs.github.com/spec/v1
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oid sha256:515d91afcfdd4ffaccd8dff308a92766c5f64db77ed38f90b4ba17fe9f66ae09
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size 326432
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pred_logit_test.npy
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version https://git-lfs.github.com/spec/v1
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oid sha256:5d3062802296c6afefef5c4e321e7a68cd3be760c2c228def7dfa921b6b9cd1d
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size 148016
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pred_logit_train.npy
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version https://git-lfs.github.com/spec/v1
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oid sha256:a3adaa2dea82eb143bea7578da601c7303fc71183d7b1dc5143e2a8285263064
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size 2452640
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preprocessor_config.json
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{
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"do_normalize": true,
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"feature_extractor_type": "Wav2Vec2FeatureExtractor",
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0,
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"return_attention_mask": true,
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"sampling_rate": 16000
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}
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test_results.json
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{
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"epoch": 10.0,
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"test_accuracy": 0.8980850373255437,
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"test_loss": 0.5234816074371338,
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"test_runtime": 16.7699,
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"test_samples_per_second": 183.722,
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"test_steps_per_second": 0.775
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}
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train_results.json
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{
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"epoch": 10.0,
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"train_accuracy": 0.9925040122127843,
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"train_loss": 0.03099818341434002,
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+
"train_runtime": 461.453,
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"train_samples_per_second": 110.724,
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"train_steps_per_second": 27.682
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}
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trainer_state.json
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