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loading configuration file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/config.json from cache at /home/sagrilaft/.cache/huggingface/transformers/dabc27df63e37bd2a7a221c7774e35f36a280fbdf917cf54cadfc7df8c786f6f.a3e4c3c967d9985881e0ae550a5f6f668f897db5ab2e0802f9b97973b15970e6
Model config Wav2Vec2Config {
  "_name_or_path": "facebook/wav2vec2-xls-r-300m",
  "activation_dropout": 0.0,
  "adapter_kernel_size": 3,
  "adapter_stride": 2,
  "add_adapter": false,
  "apply_spec_augment": true,
  "architectures": [
    "Wav2Vec2ForPreTraining"
  ],
  "attention_dropout": 0.1,
  "bos_token_id": 1,
  "classifier_proj_size": 256,
  "codevector_dim": 768,
  "contrastive_logits_temperature": 0.1,
  "conv_bias": true,
  "conv_dim": [
    512,
    512,
    512,
    512,
    512,
    512,
    512
  ],
  "conv_kernel": [
    10,
    3,
    3,
    3,
    3,
    2,
    2
  ],
  "conv_stride": [
    5,
    2,
    2,
    2,
    2,
    2,
    2
  ],
  "ctc_loss_reduction": "sum",
  "ctc_zero_infinity": false,
  "diversity_loss_weight": 0.1,
  "do_stable_layer_norm": true,
  "eos_token_id": 2,
  "feat_extract_activation": "gelu",
  "feat_extract_dropout": 0.0,
  "feat_extract_norm": "layer",
  "feat_proj_dropout": 0.1,
  "feat_quantizer_dropout": 0.0,
  "final_dropout": 0.0,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout": 0.1,
  "hidden_size": 1024,
  "initializer_range": 0.02,
  "intermediate_size": 4096,
  "layer_norm_eps": 1e-05,
  "layerdrop": 0.1,
  "mask_feature_length": 10,
  "mask_feature_min_masks": 0,
  "mask_feature_prob": 0.0,
  "mask_time_length": 10,
  "mask_time_min_masks": 2,
  "mask_time_prob": 0.075,
  "model_type": "wav2vec2",
  "num_adapter_layers": 3,
  "num_attention_heads": 16,
  "num_codevector_groups": 2,
  "num_codevectors_per_group": 320,
  "num_conv_pos_embedding_groups": 16,
  "num_conv_pos_embeddings": 128,
  "num_feat_extract_layers": 7,
  "num_hidden_layers": 24,
  "num_negatives": 100,
  "output_hidden_size": 1024,
  "pad_token_id": 0,
  "proj_codevector_dim": 768,
  "tdnn_dilation": [
    1,
    2,
    3,
    1,
    1
  ],
  "tdnn_dim": [
    512,
    512,
    512,
    512,
    1500
  ],
  "tdnn_kernel": [
    5,
    3,
    3,
    1,
    1
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.16.0.dev0",
  "use_weighted_layer_sum": false,
  "vocab_size": 32,
  "xvector_output_dim": 512
}


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Didn't find file ./tokenizer_config.json. We won't load it.
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Didn't find file ./special_tokens_map.json. We won't load it.
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loading file ./vocab.json
loading file None
loading file None
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file ./config.json not found
Adding <s> to the vocabulary
Adding </s> to the vocabulary
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/config.json from cache at /home/sagrilaft/.cache/huggingface/transformers/dabc27df63e37bd2a7a221c7774e35f36a280fbdf917cf54cadfc7df8c786f6f.a3e4c3c967d9985881e0ae550a5f6f668f897db5ab2e0802f9b97973b15970e6
Model config Wav2Vec2Config {
  "_name_or_path": "facebook/wav2vec2-xls-r-300m",
  "activation_dropout": 0.0,
  "adapter_kernel_size": 3,
  "adapter_stride": 2,
  "add_adapter": false,
  "apply_spec_augment": true,
  "architectures": [
    "Wav2Vec2ForPreTraining"
  ],
  "attention_dropout": 0.1,
  "bos_token_id": 1,
  "classifier_proj_size": 256,
  "codevector_dim": 768,
  "contrastive_logits_temperature": 0.1,
  "conv_bias": true,
  "conv_dim": [
    512,
    512,
    512,
    512,
    512,
    512,
    512
  ],
  "conv_kernel": [
    10,
    3,
    3,
    3,
    3,
    2,
    2
  ],
  "conv_stride": [
    5,
    2,
    2,
    2,
    2,
    2,
    2
  ],
  "ctc_loss_reduction": "sum",
  "ctc_zero_infinity": false,
  "diversity_loss_weight": 0.1,
  "do_stable_layer_norm": true,
  "eos_token_id": 2,
  "feat_extract_activation": "gelu",
  "feat_extract_dropout": 0.0,
  "feat_extract_norm": "layer",
  "feat_proj_dropout": 0.1,
  "feat_quantizer_dropout": 0.0,
  "final_dropout": 0.0,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout": 0.1,
  "hidden_size": 1024,
  "initializer_range": 0.02,
  "intermediate_size": 4096,
  "layer_norm_eps": 1e-05,
  "layerdrop": 0.1,
  "mask_feature_length": 10,
  "mask_feature_min_masks": 0,
  "mask_feature_prob": 0.0,
  "mask_time_length": 10,
  "mask_time_min_masks": 2,
  "mask_time_prob": 0.075,
  "model_type": "wav2vec2",
  "num_adapter_layers": 3,
  "num_attention_heads": 16,
  "num_codevector_groups": 2,
  "num_codevectors_per_group": 320,
  "num_conv_pos_embedding_groups": 16,
  "num_conv_pos_embeddings": 128,
  "num_feat_extract_layers": 7,
  "num_hidden_layers": 24,
  "num_negatives": 100,
  "output_hidden_size": 1024,
  "pad_token_id": 0,
  "proj_codevector_dim": 768,
  "tdnn_dilation": [
    1,
    2,
    3,
    1,
    1
  ],
  "tdnn_dim": [
    512,
    512,
    512,
    512,
    1500
  ],
  "tdnn_kernel": [
    5,
    3,
    3,
    1,
    1
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.16.0.dev0",
  "use_weighted_layer_sum": false,
  "vocab_size": 32,
  "xvector_output_dim": 512
}

loading feature extractor configuration file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/preprocessor_config.json from cache at /home/sagrilaft/.cache/huggingface/transformers/6fb028b95b394059e7d3b367bbca2382b576c66aebe896f04d2cd34e1b575f5b.d4484dc1c81456a2461485e7168b04347a7b9a4e3b1ef3aba723323b33e12326
Feature extractor Wav2Vec2FeatureExtractor {
  "do_normalize": true,
  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
  "feature_size": 1,
  "padding_side": "right",
  "padding_value": 0,
  "return_attention_mask": true,
  "sampling_rate": 16000
}

loading weights file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/pytorch_model.bin from cache at /home/sagrilaft/.cache/huggingface/transformers/1e6a6507f3b689035cd4b247e2a37c154e27f39143f31357a49b4e38baeccc36.1edb32803799e27ed554eb7dd935f6745b1a0b17b0ea256442fe24db6eb546cd
Some weights of the model checkpoint at facebook/wav2vec2-xls-r-300m were not used when initializing Wav2Vec2ForCTC: ['project_q.bias', 'project_q.weight', 'quantizer.weight_proj.weight', 'project_hid.bias', 'project_hid.weight', 'quantizer.codevectors', 'quantizer.weight_proj.bias']
- This IS expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-xls-r-300m and are newly initialized: ['lm_head.bias', 'lm_head.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.

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Configuration saved in ./preprocessor_config.json
tokenizer config file saved in ./tokenizer_config.json
Special tokens file saved in ./special_tokens_map.json
added tokens file saved in ./added_tokens.json
Configuration saved in ./config.json
loading feature extractor configuration file ./preprocessor_config.json
loading configuration file ./config.json
Model config Wav2Vec2Config {
  "_name_or_path": "./",
  "activation_dropout": 0.0,
  "adapter_kernel_size": 3,
  "adapter_stride": 2,
  "add_adapter": false,
  "apply_spec_augment": true,
  "architectures": [
    "Wav2Vec2ForPreTraining"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 1,
  "classifier_proj_size": 256,
  "codevector_dim": 768,
  "contrastive_logits_temperature": 0.1,
  "conv_bias": true,
  "conv_dim": [
    512,
    512,
    512,
    512,
    512,
    512,
    512
  ],
  "conv_kernel": [
    10,
    3,
    3,
    3,
    3,
    2,
    2
  ],
  "conv_stride": [
    5,
    2,
    2,
    2,
    2,
    2,
    2
  ],
  "ctc_loss_reduction": "mean",
  "ctc_zero_infinity": false,
  "diversity_loss_weight": 0.1,
  "do_stable_layer_norm": true,
  "eos_token_id": 2,
  "feat_extract_activation": "gelu",
  "feat_extract_dropout": 0.0,
  "feat_extract_norm": "layer",
  "feat_proj_dropout": 0.1,
  "feat_quantizer_dropout": 0.0,
  "final_dropout": 0.0,
  "hidden_act": "gelu",
  "hidden_dropout": 0.0,
  "hidden_size": 1024,
  "initializer_range": 0.02,
  "intermediate_size": 4096,
  "layer_norm_eps": 1e-05,
  "layerdrop": 0.0,
  "mask_feature_length": 10,
  "mask_feature_min_masks": 0,
  "mask_feature_prob": 0.0,
  "mask_time_length": 10,
  "mask_time_min_masks": 2,
  "mask_time_prob": 0.1,
  "model_type": "wav2vec2",
  "num_adapter_layers": 3,
  "num_attention_heads": 16,
  "num_codevector_groups": 2,
  "num_codevectors_per_group": 320,
  "num_conv_pos_embedding_groups": 16,
  "num_conv_pos_embeddings": 128,
  "num_feat_extract_layers": 7,
  "num_hidden_layers": 24,
  "num_negatives": 100,
  "output_hidden_size": 1024,
  "pad_token_id": 36,
  "proj_codevector_dim": 768,
  "tdnn_dilation": [
    1,
    2,
    3,
    1,
    1
  ],
  "tdnn_dim": [
    512,
    512,
    512,
    512,
    1500
  ],
  "tdnn_kernel": [
    5,
    3,
    3,
    1,
    1
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.16.0.dev0",
  "use_weighted_layer_sum": false,
  "vocab_size": 39,
  "xvector_output_dim": 512
}

loading feature extractor configuration file ./preprocessor_config.json
Feature extractor Wav2Vec2FeatureExtractor {
  "do_normalize": true,
  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
  "feature_size": 1,
  "padding_side": "right",
  "padding_value": 0,
  "return_attention_mask": true,
  "sampling_rate": 16000
}

Didn't find file ./tokenizer.json. We won't load it.
loading file ./vocab.json
loading file ./tokenizer_config.json
loading file ./added_tokens.json
loading file ./special_tokens_map.json
loading file None
Adding <s> to the vocabulary
Adding </s> to the vocabulary
/home/sagrilaft/Project/audio/xls-r-et/./ is already a clone of https://huggingface.co/shpotes/xls-r-et. Make sure you pull the latest changes with `repo.git_pull()`.
Using amp half precision backend
The following columns in the training set  don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.
***** Running training *****
  Num examples = 5705
  Num Epochs = 500
  Instantaneous batch size per device = 80
  Total train batch size (w. parallel, distributed & accumulation) = 160
  Gradient Accumulation steps = 2
  Total optimization steps = 18000
Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"
wandb: Currently logged in as: shpotes (use `wandb login --relogin` to force relogin)
wandb: Tracking run with wandb version 0.12.9
wandb: Syncing run cosine+drop_proj+low_specaugment-300M
wandb:  View project at https://wandb.ai/shpotes/xls-r-estonian
wandb:  View run at https://wandb.ai/shpotes/xls-r-estonian/runs/1xdiy2kf
wandb: Run data is saved locally in /home/sagrilaft/Project/audio/xls-r-et/wandb/run-20220126_105847-1xdiy2kf
wandb: Run `wandb offline` to turn off syncing.

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  2% 400/18000 [1:02:42<51:16:29, 10.49s/it]
                                            

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  2% 414/18000 [1:04:53<53:05:33, 10.87s/it]
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  2% 421/18000 [1:05:56<48:16:48,  9.89s/it]
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  2% 423/18000 [1:06:20<53:13:22, 10.90s/it]
  2% 424/18000 [1:06:29<50:26:10, 10.33s/it]
  2% 425/18000 [1:06:37<47:08:56,  9.66s/it]
  2% 426/18000 [1:06:44<43:19:15,  8.87s/it]
  2% 427/18000 [1:06:50<38:33:18,  7.90s/it]
  2% 428/18000 [1:06:54<33:33:27,  6.88s/it]
  2% 429/18000 [1:07:09<44:43:15,  9.16s/it]
  2% 430/18000 [1:07:19<46:00:07,  9.43s/it]
  2% 431/18000 [1:07:26<43:11:33,  8.85s/it]
  2% 432/18000 [1:07:30<34:56:30,  7.16s/it]
  2% 433/18000 [1:07:46<48:49:24, 10.01s/it]
  2% 434/18000 [1:08:00<53:38:05, 10.99s/it]
  2% 435/18000 [1:08:10<53:09:03, 10.89s/it]
  2% 436/18000 [1:08:19<50:38:26, 10.38s/it]
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  2% 438/18000 [1:08:34<42:52:00,  8.79s/it]
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  2% 440/18000 [1:08:44<33:10:31,  6.80s/it]
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  2% 442/18000 [1:09:14<52:47:34, 10.82s/it]
  2% 443/18000 [1:09:25<52:43:24, 10.81s/it]
  2% 444/18000 [1:09:34<50:46:19, 10.41s/it]
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  2% 449/18000 [1:10:17<48:02:46,  9.86s/it]
  2% 450/18000 [1:10:30<53:38:52, 11.00s/it]
  3% 451/18000 [1:10:41<53:33:23, 10.99s/it]
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  3% 500/18000 [1:18:10<33:36:35,  6.91s/it]
                                            

  3% 500/18000 [1:18:10<33:36:35,  6.91s/it]The following columns in the evaluation set  don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.
***** Running Evaluation *****
  Num examples = 2609
  Batch size = 80




  0% 0/33 [00:00<?, ?it/s]


  6% 2/33 [00:04<01:10,  2.26s/it]


  9% 3/33 [00:08<01:33,  3.13s/it]


 12% 4/33 [00:12<01:39,  3.44s/it]


 15% 5/33 [00:16<01:42,  3.64s/it]


 18% 6/33 [00:20<01:42,  3.79s/it]


 21% 7/33 [00:24<01:38,  3.80s/it]


 24% 8/33 [00:28<01:36,  3.85s/it]


 27% 9/33 [00:32<01:33,  3.88s/it]


 30% 10/33 [00:37<01:33,  4.07s/it]


 33% 11/33 [00:41<01:29,  4.06s/it]


 36% 12/33 [00:45<01:24,  4.04s/it]


 39% 13/33 [00:49<01:19,  3.98s/it]


 42% 14/33 [00:53<01:16,  4.03s/it]


 45% 15/33 [00:57<01:12,  4.04s/it]


 48% 16/33 [01:01<01:10,  4.17s/it]


 52% 17/33 [01:06<01:09,  4.32s/it]


 55% 18/33 [01:10<01:03,  4.24s/it]


 58% 19/33 [01:14<00:59,  4.24s/it]


 61% 20/33 [01:19<00:55,  4.31s/it]


 64% 21/33 [01:23<00:52,  4.34s/it]


 67% 22/33 [01:27<00:47,  4.33s/it]


 70% 23/33 [01:32<00:43,  4.38s/it]


 73% 24/33 [01:36<00:39,  4.39s/it]


 76% 25/33 [01:41<00:35,  4.42s/it]


 79% 26/33 [01:45<00:30,  4.37s/it]


 82% 27/33 [01:49<00:25,  4.31s/it]


 85% 28/33 [01:54<00:21,  4.34s/it]


 88% 29/33 [01:57<00:16,  4.09s/it]


 91% 30/33 [02:00<00:11,  3.70s/it]


 94% 31/33 [02:03<00:06,  3.40s/it]


 97% 32/33 [02:05<00:03,  3.18s/it]


100% 33/33 [02:07<00:00,  2.61s/it]

                                   

                                            



100% 33/33 [02:08<00:00,  2.61s/it]
  3% 500/18000 [1:20:23<33:36:35,  6.91s/it]

                                   Saving model checkpoint to ./checkpoint-500
Configuration saved in ./checkpoint-500/config.json
Model weights saved in ./checkpoint-500/pytorch_model.bin
Configuration saved in ./checkpoint-500/preprocessor_config.json
Configuration saved in ./preprocessor_config.json