hubert-L¶
86.4% passed tests (329 passed / 52 failed).
Topic |
Passed Tests |
|---|---|
73.0% |
|
66.7% |
|
88.9% |
|
100.0% |
|
100.0% |
|
100.0% |
|
83.3% |
|
88.9% |
|
100.0% |
|
82.1% |
|
41.7% |
|
100.0% |
|
50.0% |
|
16.7% |
|
90.0% |
|
87.5% |
Entry |
Value |
|---|---|
data |
msp-2.4.0 |
model |
facebook/hubert-large-ll60k |
sampling_rate |
16000 |
Entry |
Value |
|---|---|
Author |
jwagner |
Date |
2022-01-17 |
Name |
onnx |
Subgroup |
ser.dimensions.hubert |
Version |
1.1.0 |
Config |
{‘return_dict’: True, ‘output_hidden_states’: False, ‘output_attentions’: False, ‘torchscript’: False, ‘torch_dtype’: ‘float32’, ‘use_bfloat16’: False, ‘pruned_heads’: {}, ‘tie_word_embeddings’: True, ‘is_encoder_decoder’: False, ‘is_decoder’: False, ‘cross_attention_hidden_size’: None, ‘add_cross_attention’: False, ‘tie_encoder_decoder’: False, ‘max_length’: 20, ‘min_length’: 0, ‘do_sample’: False, ‘early_stopping’: False, ‘num_beams’: 1, ‘num_beam_groups’: 1, ‘diversity_penalty’: 0.0, ‘temperature’: 1.0, ‘top_k’: 50, ‘top_p’: 1.0, ‘repetition_penalty’: 1.0, ‘length_penalty’: 1.0, ‘no_repeat_ngram_size’: 0, ‘encoder_no_repeat_ngram_size’: 0, ‘bad_words_ids’: None, ‘num_return_sequences’: 1, ‘chunk_size_feed_forward’: 0, ‘output_scores’: False, ‘return_dict_in_generate’: False, ‘forced_bos_token_id’: None, ‘forced_eos_token_id’: None, ‘remove_invalid_values’: False, ‘architectures’: [‘HubertForSpeechClassification’], ‘finetuning_task’: ‘wav2vec2_reg’, ‘id2label’: {0: ‘LABEL_0’, 1: ‘LABEL_1’, 2: ‘LABEL_2’}, ‘label2id’: {‘LABEL_0’: 0, ‘LABEL_1’: 1, ‘LABEL_2’: 2}, ‘tokenizer_class’: ‘Wav2Vec2CTCTokenizer’, ‘prefix’: None, ‘bos_token_id’: 1, ‘pad_token_id’: 0, ‘eos_token_id’: 2, ‘sep_token_id’: None, ‘decoder_start_token_id’: None, ‘task_specific_params’: None, ‘problem_type’: ‘regression’, ‘_name_or_path’: ‘/scratch/jwagner/git/transformers/wav2vec/49_adv_hubert-large-ll60k_msp/model/adv/checkpoint-10500’, ‘transformers_version’: ‘4.13.0.dev0’, ‘feat_extract_dropout’: 0.0, ‘gradient_checkpointing’: False, ‘mask_channel_length’: 10, ‘mask_channel_min_space’: 1, ‘mask_channel_other’: 0.0, ‘mask_channel_prob’: 0.0, ‘mask_channel_selection’: ‘static’, ‘mask_time_min_space’: 1, ‘mask_time_other’: 0.0, ‘mask_time_selection’: ‘static’, ‘model_type’: ‘hubert’, ‘num_feat_extract_layers’: 7, ‘pooling_mode’: ‘mean’, ‘hidden_size’: 1024, ‘feat_extract_norm’: ‘layer’, ‘feat_extract_activation’: ‘gelu’, ‘conv_dim’: [512, 512, 512, 512, 512, 512, 512], ‘conv_stride’: [5, 2, 2, 2, 2, 2, 2], ‘conv_kernel’: [10, 3, 3, 3, 3, 2, 2], ‘conv_bias’: True, ‘num_conv_pos_embeddings’: 128, ‘num_conv_pos_embedding_groups’: 16, ‘num_hidden_layers’: 24, ‘intermediate_size’: 4096, ‘hidden_act’: ‘gelu’, ‘num_attention_heads’: 16, ‘hidden_dropout’: 0.1, ‘attention_dropout’: 0.1, ‘activation_dropout’: 0.0, ‘feat_proj_layer_norm’: True, ‘feat_proj_dropout’: 0.1, ‘final_dropout’: 0.0, ‘layerdrop’: 0.1, ‘layer_norm_eps’: 1e-05, ‘initializer_range’: 0.02, ‘vocab_size’: 32, ‘do_stable_layer_norm’: True, ‘use_weighted_layer_sum’: False, ‘classifier_proj_size’: 256, ‘apply_spec_augment’: True, ‘mask_time_prob’: 0.075, ‘mask_time_length’: 10, ‘mask_time_min_masks’: 2, ‘mask_feature_prob’: 0.0, ‘mask_feature_length’: 10, ‘mask_feature_min_masks’: 0, ‘ctc_loss_reduction’: ‘sum’, ‘ctc_zero_infinity’: False} |
Sample |
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Benchmark |
{‘ser.msppodcast.regression’: {‘arousal’: {‘1.0.0’: {60: {‘Mean Absolute Error’: 0.517090793208254, ‘Mean Squared Error’: 0.4383327781927271, ‘Pearson Correlation Coefficient’: 0.7392246118290777, ‘Concordance Correlation Coefficient’: 0.7388240825444686}}}, ‘dominance’: {‘1.0.0’: {32: {‘Mean Absolute Error’: 0.4769406201522445, ‘Mean Squared Error’: 0.36761703897357734, ‘Pearson Correlation Coefficient’: 0.6633787549838513, ‘Concordance Correlation Coefficient’: 0.6550225676991565}}}, ‘valence’: {‘1.0.0’: {72: {‘Mean Absolute Error’: 0.6349289235970057, ‘Mean Squared Error’: 0.6593258104286702, ‘Pearson Correlation Coefficient’: 0.6369527257032744, ‘Concordance Correlation Coefficient’: 0.6357127791742279}}}}} |