jonatasgrosman
commited on
Commit
•
1374a29
1
Parent(s):
4c59763
update model
Browse files- README.md +17 -10
- config.json +19 -4
- preprocessor_config.json +1 -0
- pytorch_model.bin +2 -2
- vocab.json +1 -1
README.md
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@@ -24,10 +24,10 @@ model-index:
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metrics:
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- name: Test WER
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type: wer
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value:
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- name: Test CER
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type: cer
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value:
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---
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# Wav2Vec2-Large-XLSR-53-Dutch
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@@ -49,7 +49,7 @@ from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
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LANG_ID = "nl"
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MODEL_ID = "jonatasgrosman/wav2vec2-large-xlsr-53-dutch"
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SAMPLES =
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test_dataset = load_dataset("common_voice", LANG_ID, split=f"test[:{SAMPLES}]")
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@@ -81,11 +81,16 @@ for i, predicted_sentence in enumerate(predicted_sentences):
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| Reference | Prediction |
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| ------------- | ------------- |
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-
| DE ABORIGINALS ZIJN DE OORSPRONKELIJKE BEWONERS VAN AUSTRALIË. | DE
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| MIJN TOETSENBORD ZIT VOL STOF | MIJN
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| ZE HAD DE BANK BESCHADIGD MET HAAR SKATEBOARD. | ZE HAD DE BANK BESCHADIGD MET HAAR SCHEETBOORD |
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| WAAR LAAT JIJ JE ONDERHOUD DOEN? | WAAR LAAT JIJ
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| NA HET LEZEN VAN VELE BEOORDELINGEN HAD ZE EINDELIJK HAAR OOG LATEN VALLEN OP EEN LAPTOP MET EEN QWERTY TOETSENBORD. | NA HET LEZEN VAN VELE BEOORDELINGEN HAD ZE EINDELIJK HAAR OOG LATEN VALLEN OP EEN LAPTOP MET EEN
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## Evaluation
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MODEL_ID = "jonatasgrosman/wav2vec2-large-xlsr-53-dutch"
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DEVICE = "cuda"
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-
CHARS_TO_IGNORE = [",", "?", "¿", ".", "!", "¡", ";", ":", '""', "%", '"', "�", "ʿ", "·", "჻", "~", "՞",
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"؟", "،", "।", "॥", "«", "»", "„", "“", "”", "「", "」", "‘", "’", "《", "》", "(", ")", "[", "]",
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"=", "`", "_", "+", "<", ">", "…", "–", "°", "´", "ʾ", "‹", "›", "©", "®", "—", "→", "。"
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test_dataset = load_dataset("common_voice", LANG_ID, split="test")
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| Model | WER | CER |
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| ------------- | ------------- | ------------- |
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-
| jonatasgrosman/wav2vec2-large-xlsr-53-dutch | **
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| wietsedv/wav2vec2-large-xlsr-53-dutch | 16.78% | 5.60% |
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| facebook/wav2vec2-large-xlsr-53-dutch | 20.97% | 7.24% |
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| nithinholla/wav2vec2-large-xlsr-53-dutch | 21.39% | 7.29% |
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metrics:
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- name: Test WER
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type: wer
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value: 15.76
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- name: Test CER
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type: cer
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value: 5.50
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---
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# Wav2Vec2-Large-XLSR-53-Dutch
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LANG_ID = "nl"
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MODEL_ID = "jonatasgrosman/wav2vec2-large-xlsr-53-dutch"
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SAMPLES = 10
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test_dataset = load_dataset("common_voice", LANG_ID, split=f"test[:{SAMPLES}]")
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| Reference | Prediction |
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| ------------- | ------------- |
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| DE ABORIGINALS ZIJN DE OORSPRONKELIJKE BEWONERS VAN AUSTRALIË. | DE ABBORIGENALS ZIJN DE OORSPRONKELIJKE BEWONERS VAN AUSTRALIË |
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| MIJN TOETSENBORD ZIT VOL STOF. | MIJN TOETSENBORD ZIT VOL STOF |
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| ZE HAD DE BANK BESCHADIGD MET HAAR SKATEBOARD. | ZE HAD DE BANK BESCHADIGD MET HAAR SCHEETBOORD |
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| WAAR LAAT JIJ JE ONDERHOUD DOEN? | WAAR LAAT JIJ HET ONDERHOUD DOEN |
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| NA HET LEZEN VAN VELE BEOORDELINGEN HAD ZE EINDELIJK HAAR OOG LATEN VALLEN OP EEN LAPTOP MET EEN QWERTY TOETSENBORD. | NA HET LEZEN VAN VELE BEOORDELINGEN HAD ZE EINDELIJK HAAR OOG LATEN VALLEN OP EEN LAPTOP MET EEN QUERTITOETSEMBORD |
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| DE TAMPONS ZIJN OP. | DE TAPONT ZIJN OP |
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| MARIJKE KENT OLIVIER NU AL MEER DAN TWEE JAAR. | MAARRIJKEN KENT OLIEVIER NU AL MEER DAN TWEE JAAR |
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| HET VOEREN VAN BROOD AAN EENDEN IS EIGENLIJK ONGEZOND VOOR DE BEESTEN. | HET VOEREN VAN BEUROT AAN EINDEN IS EIGENLIJK ONGEZOND VOOR DE BEESTEN |
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| PARKET MOET JE STOFZUIGEN, TEGELS MOET JE DWEILEN. | PARKET MOET JE STOF ZUIGEN MAAR TEGELS MOET JE DWEILEN |
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| IN ONZE BUURT KENT IEDEREEN ELKAAR. | IN ONZE BUURT KENT IEDEREEN ELKAAR |
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## Evaluation
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MODEL_ID = "jonatasgrosman/wav2vec2-large-xlsr-53-dutch"
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DEVICE = "cuda"
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CHARS_TO_IGNORE = [",", "?", "¿", ".", "!", "¡", ";", ";", ":", '""', "%", '"', "�", "ʿ", "·", "჻", "~", "՞",
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"؟", "،", "।", "॥", "«", "»", "„", "“", "”", "「", "」", "‘", "’", "《", "》", "(", ")", "[", "]",
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"{", "}", "=", "`", "_", "+", "<", ">", "…", "–", "°", "´", "ʾ", "‹", "›", "©", "®", "—", "→", "。",
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"、", "﹂", "﹁", "‧", "~", "﹏", ",", "{", "}", "(", ")", "[", "]", "【", "】", "‥", "〽",
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"『", "』", "〝", "〟", "⟨", "⟩", "〜", ":", "!", "?", "♪", "؛", "/", "\\", "º", "−", "^", "ʻ", "ˆ"]
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test_dataset = load_dataset("common_voice", LANG_ID, split="test")
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| Model | WER | CER |
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| ------------- | ------------- | ------------- |
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| jonatasgrosman/wav2vec2-large-xlsr-53-dutch | **15.76%** | **5.50%** |
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| wietsedv/wav2vec2-large-xlsr-53-dutch | 16.78% | 5.60% |
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| facebook/wav2vec2-large-xlsr-53-dutch | 20.97% | 7.24% |
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| nithinholla/wav2vec2-large-xlsr-53-dutch | 21.39% | 7.29% |
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config.json
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],
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"attention_dropout": 0.1,
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"bos_token_id": 1,
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"conv_bias": true,
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"conv_dim": [
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512,
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],
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"ctc_loss_reduction": "mean",
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"ctc_zero_infinity": true,
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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": 0.05,
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-
"
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"gradient_checkpointing": true,
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"hidden_act": "gelu",
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"hidden_dropout": 0.05,
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"hidden_dropout_prob": 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": 0.05,
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"mask_feature_length": 10,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_prob": 0.05,
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"model_type": "wav2vec2",
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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": 24,
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"pad_token_id": 0,
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"
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"
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}
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],
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"attention_dropout": 0.1,
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"bos_token_id": 1,
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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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],
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"ctc_loss_reduction": "mean",
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"ctc_zero_infinity": true,
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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": 0.05,
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"feat_quantizer_dropout": 0.0,
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"final_dropout": 0.0,
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"gradient_checkpointing": true,
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"hidden_act": "gelu",
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"hidden_dropout": 0.05,
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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": 0.05,
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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_prob": 0.0,
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"mask_time_length": 10,
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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_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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"pad_token_id": 0,
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"proj_codevector_dim": 768,
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"transformers_version": "4.7.0.dev0",
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"vocab_size": 39
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}
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preprocessor_config.json
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{
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"do_normalize": true,
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0.0,
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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": 0.0,
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:f307fd2a7a323dbc4dc6fda728e97d51c0be50fed198cb4d1a14d275acb255cd
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size 1262093720
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vocab.json
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{"<pad>": 0, "<s>": 1, "</s>": 2, "<unk>": 3, "
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{"<pad>": 0, "<s>": 1, "</s>": 2, "<unk>": 3, "|": 4, "'": 5, "-": 6, "A": 7, "B": 8, "C": 9, "D": 10, "E": 11, "F": 12, "G": 13, "H": 14, "I": 15, "J": 16, "K": 17, "L": 18, "M": 19, "N": 20, "O": 21, "P": 22, "Q": 23, "R": 24, "S": 25, "T": 26, "U": 27, "V": 28, "W": 29, "X": 30, "Y": 31, "Z": 32, "É": 33, "Ë": 34, "Ï": 35, "Ó": 36, "Ö": 37, "Ü": 38}
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