| wandb: Currently logged in as: priyanshi-pal (priyanshipal). Use `wandb login --relogin` to force relogin |
| wandb: wandb version 0.17.7 is available! To upgrade, please run: |
| wandb: $ pip install wandb --upgrade |
| wandb: Tracking run with wandb version 0.17.6 |
| wandb: Run data is saved locally in /scratch/elec/t405-puhe/p/palp3/MUCS/wandb/run-20240822_172108-s5ed6d0k |
| wandb: Run `wandb offline` to turn off syncing. |
| wandb: Syncing run eval_pd2000_s300_shuff500_hindi |
| wandb: ⭐️ View project at https://wandb.ai/priyanshipal/huggingface |
| wandb: 🚀 View run at https://wandb.ai/priyanshipal/huggingface/runs/s5ed6d0k |
| /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/training_args.py:1525: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead |
| warnings.warn( |
|
Generating train split: 0 examples [00:00, ? examples/s]
Generating train split: 2564 examples [00:00, 6589.90 examples/s]
Generating train split: 2564 examples [00:00, 6548.28 examples/s] |
| /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/models/auto/configuration_auto.py:957: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead. |
| warnings.warn( |
| /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/models/auto/feature_extraction_auto.py:329: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead. |
| warnings.warn( |
| Wav2Vec2CTCTokenizer(name_or_path='', vocab_size=149, model_max_length=1000000000000000019884624838656, is_fast=False, padding_side='right', truncation_side='right', special_tokens={'bos_token': '<s>', 'eos_token': '</s>', 'unk_token': '[UNK]', 'pad_token': '[PAD]'}, clean_up_tokenization_spaces=True), added_tokens_decoder={ |
| 147: AddedToken("[UNK]", rstrip=True, lstrip=True, single_word=False, normalized=False, special=False), |
| 148: AddedToken("[PAD]", rstrip=True, lstrip=True, single_word=False, normalized=False, special=False), |
| 149: AddedToken("<s>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), |
| 150: AddedToken("</s>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True), |
| } |
| CHECK MODEL PARAMS Wav2Vec2ForCTC( |
| (wav2vec2): Wav2Vec2Model( |
| (feature_extractor): Wav2Vec2FeatureEncoder( |
| (conv_layers): ModuleList( |
| (0): Wav2Vec2LayerNormConvLayer( |
| (conv): Conv1d(1, 512, kernel_size=(10,), stride=(5,)) |
| (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True) |
| (activation): GELUActivation() |
| ) |
| (1-4): 4 x Wav2Vec2LayerNormConvLayer( |
| (conv): Conv1d(512, 512, kernel_size=(3,), stride=(2,)) |
| (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True) |
| (activation): GELUActivation() |
| ) |
| (5-6): 2 x Wav2Vec2LayerNormConvLayer( |
| (conv): Conv1d(512, 512, kernel_size=(2,), stride=(2,)) |
| (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True) |
| (activation): GELUActivation() |
| ) |
| ) |
| ) |
| (feature_projection): Wav2Vec2FeatureProjection( |
| (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True) |
| (projection): Linear(in_features=512, out_features=1024, bias=True) |
| (dropout): Dropout(p=0.3, inplace=False) |
| ) |
| (encoder): Wav2Vec2EncoderStableLayerNorm( |
| (pos_conv_embed): Wav2Vec2PositionalConvEmbedding( |
| (conv): ParametrizedConv1d( |
| 1024, 1024, kernel_size=(128,), stride=(1,), padding=(64,), groups=16 |
| (parametrizations): ModuleDict( |
| (weight): ParametrizationList( |
| (0): _WeightNorm() |
| ) |
| ) |
| ) |
| (padding): Wav2Vec2SamePadLayer() |
| (activation): GELUActivation() |
| ) |
| (layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
| (dropout): Dropout(p=0.2, inplace=False) |
| (layers): ModuleList( |
| (0-23): 24 x Wav2Vec2EncoderLayerStableLayerNorm( |
| (attention): Wav2Vec2SdpaAttention( |
| (k_proj): Linear(in_features=1024, out_features=1024, bias=True) |
| (v_proj): Linear(in_features=1024, out_features=1024, bias=True) |
| (q_proj): Linear(in_features=1024, out_features=1024, bias=True) |
| (out_proj): Linear(in_features=1024, out_features=1024, bias=True) |
| ) |
| (dropout): Dropout(p=0.2, inplace=False) |
| (layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
| (feed_forward): Wav2Vec2FeedForward( |
| (intermediate_dropout): Dropout(p=0.0, inplace=False) |
| (intermediate_dense): Linear(in_features=1024, out_features=4096, bias=True) |
| (intermediate_act_fn): GELUActivation() |
| (output_dense): Linear(in_features=4096, out_features=1024, bias=True) |
| (output_dropout): Dropout(p=0.2, inplace=False) |
| ) |
| (final_layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) |
| ) |
| ) |
| ) |
| ) |
| (dropout): Dropout(p=0.0, inplace=False) |
| (lm_head): Linear(in_features=1024, out_features=151, bias=True) |
| ) |
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| /scratch/work/palp3/myenv/lib/python3.11/site-packages/accelerate/accelerator.py:488: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. |
| self.scaler = torch.cuda.amp.GradScaler(**kwargs) |
| max_steps is given, it will override any value given in num_train_epochs |
| check the eval set length 2564 |
| 08/22/2024 17:21:47 - INFO - __main__ - *** Evaluate *** |
| /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/models/wav2vec2/processing_wav2vec2.py:157: UserWarning: `as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your labels by using the argument `text` of the regular `__call__` method (either in the same call as your audio inputs, or in a separate call. |
| warnings.warn( |
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| Printing predictions for a few samples: |
| Sample 1: |
| Reference: लिबर ऑफिस impress में एक प्रस्तुति document बनाना और बुनियादी formatting के इस spoken tutorial में आपका स्वागत है |
| ###### |
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| Prediction: liber ofis impres में एक प्रस्तुति document बनाना और बुनियादी formating के इस spoken tutorial में आपका |
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| Sample 2: |
| Reference: इस tutorial में हम impress window के भागों के बारे में सीखेंगे और कैसे स्लाइड इन्सर्ट करें और कॉपी करें फॉन्ट तथा फॉन्ट को फॉर्मेट करना सीखेंगे |
| ###### |
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| Prediction: इस tutorial में हम impres windw के भागों के बारे में सीखेंगे और कैसे slide insert करें और copy करेंfornt तथा font को format करना सीखेंगे |
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| Sample 3: |
| Reference: यहाँ हम अपने ऑपरेटिंग सिस्टम के रूप में gnu/linux और लिबरऑफिस वर्जन 334 का उपयोग कर रहे हैं |
| ###### |
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| Prediction: यहाँ हम अपने operेting सिstem के रूप में gnu linixस और libr ofis version 34 का उपयोग कर रह हं |
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| Sample 4: |
| Reference: चलिए अपनी प्रस्तुति प्रेजैटेशन sample impress open करते हैं जिसे पिछले tutorial में बनाया था |
| ###### |
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| Prediction: चलिए अपनी प्रस्तुति sampal impres open करते हैं जसेपछले |
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| Sample 5: |
| Reference: चलिए देखते हैं कि screen पर क्या क्या है |
| ###### |
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| Prediction: ाया थाचलिए देखते हैं कि सकrीन पर क्या क्या है |
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| last Reference string इस mission पर अधिक जानकारी दिए गए लिंक पर उपलब्ध है |
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| last prediction string दिए गयए linक पर उपलब्ध हैspoken hypen tutorial org slaश nmct hypenintro |
| ***** eval metrics ***** |
| eval_cer = 0.3161 |
| eval_loss = 1.5929 |
| eval_model_preparation_time = 0.0054 |
| eval_runtime = 0:02:18.43 |
| eval_samples = 2564 |
| eval_samples_per_second = 18.522 |
| eval_steps_per_second = 1.163 |
| eval_wer = 0.4992 |
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