Training in progress, step 500

.gitattributes

@@ -40,3 +40,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 .venv/lib/python3.9/site-packages/torch/lib/libtorch_cuda.so filter=lfs diff=lfs merge=lfs -text
 .venv/lib/python3.9/site-packages/torch/lib/libtorch_python.so filter=lfs diff=lfs merge=lfs -text
 wandb/run-20220130_021614-39ybnrhl/run-39ybnrhl.wandb filter=lfs diff=lfs merge=lfs -text
+wandb/run-20220131_140404-gjg8nz5t/run-gjg8nz5t.wandb filter=lfs diff=lfs merge=lfs -text

README.md

@@ -4,10 +4,8 @@ language:
 license: apache-2.0
 tags:
 - automatic-speech-recognition
-- mozilla-foundation/common_voice_7_0
+- mozilla-foundation/common_voice_8_0
 - generated_from_trainer
-- et
-- robust-speech-event
 datasets:
 - common_voice
 model-index:
@@ -20,10 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # 
 
-This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - ET dataset.
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - ET dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4783
-- Wer: 0.3439
+- Loss: 0.4927
+- Wer: 0.3536
 
 ## Model description
 
@@ -58,14 +56,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.3382        | 12.5  | 500  | 0.3756          | 0.4654 |
-| 0.1941        | 25.0  | 1000 | 0.4314          | 0.4388 |
-| 0.1562        | 37.5  | 1500 | 0.4554          | 0.4155 |
-| 0.1267        | 50.0  | 2000 | 0.4749          | 0.4063 |
-| 0.1003        | 62.5  | 2500 | 0.4812          | 0.3939 |
-| 0.0751        | 75.0  | 3000 | 0.4776          | 0.3626 |
-| 0.0621        | 87.5  | 3500 | 0.4851          | 0.3497 |
-| 0.0568        | 100.0 | 4000 | 0.4783          | 0.3439 |
+| 0.3442        | 12.5  | 500  | 0.3825          | 0.4763 |
+| 0.1934        | 25.0  | 1000 | 0.4236          | 0.4414 |
+| 0.149         | 37.5  | 1500 | 0.4503          | 0.4190 |
+| 0.1253        | 50.0  | 2000 | 0.4674          | 0.4143 |
+| 0.0966        | 62.5  | 2500 | 0.4847          | 0.3925 |
+| 0.0741        | 75.0  | 3000 | 0.4745          | 0.3704 |
+| 0.0608        | 87.5  | 3500 | 0.4807          | 0.3568 |
+| 0.0541        | 100.0 | 4000 | 0.4927          | 0.3536 |
 
 
 ### Framework versions

all_results.json

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eval_results.json

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-{
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run-300M.sh

@@ -36,3 +36,5 @@ python src/run_speech_recognition_ctc_bnb.py \
        --run_name="cosine+drop_proj+low_specaugment-300M" \
        --do_train --do_eval \
        --use_auth_token --push_to_hub
+
+#       --use_auth_token --push_to_hub

train_results.json

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trainer_state.json

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wandb/run-20220130_021614-39ybnrhl/files/config.yaml

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wandb/run-20220130_021614-39ybnrhl/files/output.log

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 01/30/2022 12:06:39 - WARNING - huggingface_hub.repository - To https://huggingface.co/shpotes/xls-r-et
    3268d07e..314b5e1c  main -> main
 Dropping the following result as it does not have all the necessary fields:
+{'dataset': {'name': 'MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - ET', 'type': 'common_voice', 'args': 'Config: et, Training split: train+validation, Eval split: test'}}
+Upload file wandb/run-20220130_021614-39ybnrhl/run-39ybnrhl.wandb:   2%|██▏                                                                                                    | 608k/27.6M [00:01<00:48, 589kB/s]To https://huggingface.co/shpotes/xls-r-et
+   314b5e1c..69a8523f  main -> main
+Upload file wandb/run-20220130_021614-39ybnrhl/run-39ybnrhl.wandb: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████| 27.6M/27.6M [00:02<00:00, 14.4MB/s]
+01/30/2022 12:06:49 - WARNING - huggingface_hub.repository - To https://huggingface.co/shpotes/xls-r-et
+   314b5e1c..69a8523f  main -> main

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+2022-01-30 12:06:59,756 INFO    MainThread:2586828 [internal.py:handle_exit():77] Internal process exited

wandb/run-20220130_021614-39ybnrhl/logs/debug.log

@@ -22,3 +22,157 @@ config: {}
 2022-01-30 02:16:15,933 INFO    MainThread:2586598 [wandb_init.py:init():633] run started, returning control to user process
 2022-01-30 02:16:15,950 INFO    MainThread:2586598 [wandb_run.py:_config_callback():956] config_cb None None {'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': ['Wav2Vec2ForPreTraining'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 36, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'facebook/wav2vec2-xls-r-300m', 'transformers_version': '4.16.0.dev0', 'feat_extract_dropout': 0.0, 'model_type': 'wav2vec2', 'num_feat_extract_layers': 7, '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': 0.0, 'attention_dropout': 0.0, 'activation_dropout': 0.0, 'feat_proj_dropout': 0.1, 'final_dropout': 0.0, 'layerdrop': 0.0, 'layer_norm_eps': 1e-05, 'initializer_range': 0.02, 'vocab_size': 39, 'do_stable_layer_norm': True, 'use_weighted_layer_sum': False, 'apply_spec_augment': True, 'mask_time_prob': 0.1, 'mask_time_length': 10, 'mask_time_min_masks': 2, 'mask_feature_prob': 0.0, 'mask_feature_length': 10, 'mask_feature_min_masks': 0, 'num_codevectors_per_group': 320, 'num_codevector_groups': 2, 'contrastive_logits_temperature': 0.1, 'feat_quantizer_dropout': 0.0, 'num_negatives': 100, 'codevector_dim': 768, 'proj_codevector_dim': 768, 'diversity_loss_weight': 0.1, 'ctc_loss_reduction': 'mean', 'ctc_zero_infinity': False, 'add_adapter': False, 'adapter_kernel_size': 3, 'adapter_stride': 2, 'num_adapter_layers': 3, 'output_hidden_size': 1024, 'classifier_proj_size': 256, 'tdnn_dim': [512, 512, 512, 512, 1500], 'tdnn_kernel': [5, 3, 3, 1, 1], 'tdnn_dilation': [1, 2, 3, 1, 1], 'xvector_output_dim': 512, 'output_dir': './', 'overwrite_output_dir': True, 'do_train': True, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'steps', 'prediction_loss_only': False, 'per_device_train_batch_size': 72, 'per_device_eval_batch_size': 72, 'per_gpu_train_batch_size': 'None', 'per_gpu_eval_batch_size': 'None', 'gradient_accumulation_steps': 2, 'eval_accumulation_steps': 'None', 'learning_rate': 0.0003, 'weight_decay': 0.0, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 100.0, 'max_steps': -1, 'lr_scheduler_type': 'cosine', 'warmup_ratio': 0.0, 'warmup_steps': 500, 'log_level': -1, 'log_level_replica': -1, 'log_on_each_node': True, 'logging_dir': './runs/Jan30_02-15-54_ganymede.eafit.edu.co', 'logging_strategy': 'steps', 'logging_first_step': False, 'logging_steps': 100, 'logging_nan_inf_filter': True, 'save_strategy': 'steps', 'save_steps': 500, 'save_total_limit': 1, 'save_on_each_node': False, 'no_cuda': False, 'seed': 42, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'amp', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': 'None', 'local_rank': -1, 'xpu_backend': 'None', 'tpu_num_cores': 'None', 'tpu_metrics_debug': False, 'debug': '[]', 'dataloader_drop_last': False, 'eval_steps': 500, 'dataloader_num_workers': 0, 'past_index': -1, 'run_name': 'cosine+drop_proj+low_specaugment-300M', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': 'None', 'load_best_model_at_end': False, 'metric_for_best_model': 'None', 'greater_is_better': 'None', 'ignore_data_skip': False, 'sharded_ddp': '[]', 'deepspeed': 'None', 'label_smoothing_factor': 0.0, 'optim': 'adamw_hf', 'adafactor': False, 'group_by_length': True, 'length_column_name': 'input_length', 'report_to': "['wandb']", 'ddp_find_unused_parameters': 'None', 'ddp_bucket_cap_mb': 'None', 'dataloader_pin_memory': True, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': True, 'resume_from_checkpoint': 'None', 'hub_model_id': 'None', 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'gradient_checkpointing': True, 'fp16_backend': 'auto', 'push_to_hub_model_id': 'None', 'push_to_hub_organization': 'None', 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', '_n_gpu': 1, 'mp_parameters': '', 'train_batch_size': 72, 'eval_batch_size': 72}
 2022-01-30 02:16:15,953 INFO    MainThread:2586598 [wandb_watch.py:watch():43] Watching
+2022-01-30 12:06:52,264 INFO    MainThread:2586598 [wandb_run.py:_atexit_cleanup():1780] got exitcode: 0
+2022-01-30 12:06:52,266 INFO    MainThread:2586598 [wandb_run.py:_restore():1752] restore
+2022-01-30 12:06:54,568 INFO    MainThread:2586598 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 1
+}
+pusher_stats {
+  uploaded_bytes: 2324
+  total_bytes: 2324
+}
+
+2022-01-30 12:06:54,725 INFO    MainThread:2586598 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 1
+}
+pusher_stats {
+  uploaded_bytes: 2324
+  total_bytes: 2324
+}
+
+2022-01-30 12:06:55,437 INFO    MainThread:2586598 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 1
+}
+pusher_stats {
+  uploaded_bytes: 2324
+  total_bytes: 2324
+}
+
+2022-01-30 12:06:55,766 INFO    MainThread:2586598 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 2324
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+}
+
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+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 2324
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+}
+
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+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 2324
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+}
+
+2022-01-30 12:06:56,076 INFO    MainThread:2586598 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 5
+}
+pusher_stats {
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+}
+
+2022-01-30 12:06:56,179 INFO    MainThread:2586598 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 823600
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+}
+
+2022-01-30 12:06:56,282 INFO    MainThread:2586598 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 823600
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+}
+
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+  wandb_count: 5
+}
+pusher_stats {
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+}
+
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+  wandb_count: 5
+}
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+
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+  wandb_count: 5
+}
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+
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+  wandb_count: 5
+}
+pusher_stats {
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wandb/run-20220130_235926-2f5mzr6c/files/output.log

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+
+  0%|                                                                                                                                                                                    | 0/4000 [00:00<?, ?it/s]Traceback (most recent call last):
+  File "/home/sagrilaft/Project/audio/xls-r-et/src/run_speech_recognition_ctc_bnb.py", line 760, in <module>
+    main()
+  File "/home/sagrilaft/Project/audio/xls-r-et/src/run_speech_recognition_ctc_bnb.py", line 711, in main
+    train_result = trainer.train(resume_from_checkpoint=checkpoint)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/trainer.py", line 1365, in train
+    tr_loss_step = self.training_step(model, inputs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/trainer.py", line 1940, in training_step
+    loss = self.compute_loss(model, inputs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/trainer.py", line 1972, in compute_loss
+    outputs = model(**inputs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py", line 1720, in forward
+    outputs = self.wav2vec2(
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py", line 1313, in forward
+    extract_features = self.feature_extractor(input_values)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py", line 482, in forward
+    hidden_states = conv_layer(hidden_states)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py", line 357, in forward
+    hidden_states = self.layer_norm(hidden_states)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/normalization.py", line 189, in forward
+    return F.layer_norm(
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/functional.py", line 2347, in layer_norm
+    return torch.layer_norm(input, normalized_shape, weight, bias, eps, torch.backends.cudnn.enabled)
+RuntimeError: CUDA out of memory. Tried to allocate 4.71 GiB (GPU 0; 31.75 GiB total capacity; 3.62 GiB already allocated; 1.22 GiB free; 3.62 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

wandb/run-20220130_235926-2f5mzr6c/files/requirements.txt

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wandb/run-20220131_000222-2f4y0tls/files/output.log

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+
+  0%|                                                                                                                                                                                    | 0/3000 [00:00<?, ?it/s]Traceback (most recent call last):
+  File "/home/sagrilaft/Project/audio/xls-r-et/src/run_speech_recognition_ctc_bnb.py", line 760, in <module>
+    main()
+  File "/home/sagrilaft/Project/audio/xls-r-et/src/run_speech_recognition_ctc_bnb.py", line 711, in main
+    train_result = trainer.train(resume_from_checkpoint=checkpoint)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/trainer.py", line 1365, in train
+    tr_loss_step = self.training_step(model, inputs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/trainer.py", line 1940, in training_step
+    loss = self.compute_loss(model, inputs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/trainer.py", line 1972, in compute_loss
+    outputs = model(**inputs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py", line 1720, in forward
+    outputs = self.wav2vec2(
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py", line 1313, in forward
+    extract_features = self.feature_extractor(input_values)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py", line 482, in forward
+    hidden_states = conv_layer(hidden_states)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib/python3.9/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py", line 357, in forward
+    hidden_states = self.layer_norm(hidden_states)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
+    return forward_call(*input, **kwargs)
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/modules/normalization.py", line 189, in forward
+    return F.layer_norm(
+  File "/home/sagrilaft/Project/audio/xls-r-et/.venv/lib64/python3.9/site-packages/torch/nn/functional.py", line 2347, in layer_norm
+    return torch.layer_norm(input, normalized_shape, weight, bias, eps, torch.backends.cudnn.enabled)
+RuntimeError: CUDA out of memory. Tried to allocate 4.18 GiB (GPU 0; 31.75 GiB total capacity; 3.35 GiB already allocated; 1.49 GiB free; 3.35 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

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wandb/run-20220131_000222-2f4y0tls/logs/debug.log

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wandb/run-20220131_001044-248r0x8f/files/wandb-metadata.json

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+    "codePath": "src/run_speech_recognition_ctc_bnb.py",
+    "git": {
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+        "commit": "ff66b86f52be4c55fb5be74a60f889284554c939"
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+    "root": "/home/sagrilaft/Project/audio/xls-r-et",
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+ 10%|████████████████▊                                                                                                                                                       | 400/4000 [56:32<6:29:49,  6.50s/it]
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+ 12%|████████████████████▊                                                                                                                                                 | 500/4000 [1:10:56<9:45:10, 10.03s/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 = 2613
+  Batch size = 72
+{'loss': 0.3442, 'learning_rate': 0.000998, 'epoch': 12.5}
+
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+Configuration saved in ./checkpoint-500/config.json
+Model weights saved in ./checkpoint-500/pytorch_model.bin
+Configuration saved in ./checkpoint-500/preprocessor_config.json
+{'eval_loss': 0.3824974596500397, 'eval_wer': 0.47628709104742584, 'eval_runtime': 133.9974, 'eval_samples_per_second': 19.5, 'eval_steps_per_second': 0.276, 'epoch': 12.5}
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+ 15%|████████████████████████▉                                                                                                                                             | 600/4000 [1:27:09<6:07:37,  6.49s/it]
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+ 17%|█████████████████████████████                                                                                                                                         | 699/4000 [1:41:17<8:04:21,  8.80s/it]
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+ 20%|█████████████████████████████████▏                                                                                                                                    | 800/4000 [1:55:25<5:49:59,  6.56s/it]
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+ 22%|█████████████████████████████████████▎                                                                                                                                | 899/4000 [2:09:27<7:31:17,  8.73s/it]
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+ 25%|███████████████████████████████████���█████▎                                                                                                                           | 1000/4000 [2:23:35<5:34:34,  6.69s/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 = 2613
+  Batch size = 72
+{'loss': 0.1934, 'learning_rate': 0.0009506789790182364, 'epoch': 25.0}
+
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+100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 37/37 [02:07<00:00,  2.09s/it]
+Configuration saved in ./checkpoint-1000/config.json
+Model weights saved in ./checkpoint-1000/pytorch_model.bin
+Configuration saved in ./checkpoint-1000/preprocessor_config.json
+Deleting older checkpoint [checkpoint-500] due to args.save_total_limit
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+ 27%|█████████████████████████████████████████████▎                                                                                                                       | 1099/4000 [2:39:51<6:58:13,  8.65s/it]
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+ 30%|█████████████████████████████████████████████████▌                                                                                                                   | 1200/4000 [2:53:55<5:10:00,  6.64s/it]
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+ 32%|█████████████████████████████████████████████████████▋                                                                                                               | 1300/4000 [3:08:09<7:25:48,  9.91s/it]
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+ 35%|█████████████████████████████████████████████████████████▋                                                                                                           | 1399/4000 [3:21:57<5:40:57,  7.87s/it]
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+ 37%|█████████████████████████████████████████████████████████████▊                                                                                                       | 1499/4000 [3:36:00<6:04:19,  8.74s/it]
+ 38%|█████████████████████████████████████████████████████████████▉                                                                                                       | 1500/4000 [3:36:12<6:49:33,  9.83s/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 = 2613
+  Batch size = 72
+
+
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+100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 37/37 [02:07<00:00,  2.07s/it]
+
+Configuration saved in ./checkpoint-1500/config.json
+Model weights saved in ./checkpoint-1500/pytorch_model.bin
+Configuration saved in ./checkpoint-1500/preprocessor_config.json
+Deleting older checkpoint [checkpoint-1000] due to args.save_total_limit
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+ 40%|█████████████████████████████████████████████████████████████████▉                                                                                                   | 1599/4000 [3:52:16<5:12:57,  7.82s/it]
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+ 42%|██████████████████████████████████████████████████████████████████████▏                                                                                              | 1700/4000 [4:06:34<6:20:58,  9.94s/it]
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+ 45%|██████████████████████████████████████████████████████████████████████████▎                                                                                          | 1800/4000 [4:20:24<3:56:42,  6.46s/it]
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+ 48%|██████████████████████████████████████████████████████████████████████████████▍                                                                                      | 1900/4000 [4:34:41<5:44:05,  9.83s/it]
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+ 50%|██████████████████████████████████████████████████████████████████████████████████▍                                                                                  | 1999/4000 [4:48:30<4:28:04,  8.04s/it]
+ 50%|██████████████████████████████████████████████████████████████████████████████████▌                                                                                  | 2000/4000 [4:48:33<3:41:10,  6.64s/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 = 2613
+  Batch size = 72
+
+
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+Configuration saved in ./checkpoint-2000/config.json
+{'eval_loss': 0.46736055612564087, 'eval_wer': 0.41431016992137965, 'eval_runtime': 133.2229, 'eval_samples_per_second': 19.614, 'eval_steps_per_second': 0.278, 'epoch': 50.0}
+Model weights saved in ./checkpoint-2000/pytorch_model.bin
+Configuration saved in ./checkpoint-2000/preprocessor_config.json
+Deleting older checkpoint [checkpoint-1500] due to args.save_total_limit
+
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+ 52%|██████████████████████████████████████████████████████████████████████████████████████▌                                                                              | 2099/4000 [5:04:49<4:36:30,  8.73s/it]
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+ 57%|██████████████████████████████████████████████████████████████████████████████████████████████▊                                                                      | 2299/4000 [5:32:49<4:06:37,  8.70s/it]
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+ 60%|███████████████████████████████████████████████████████████████████████████████████████████████████                                                                  | 2400/4000 [5:46:47<2:47:55,  6.30s/it]
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+ 62%|███████████████████████████████████████████████████████████████████████████████████████████████████████                                                              | 2499/4000 [6:00:45<3:36:50,  8.67s/it]
+ 62%|███████████████████████████████████████████████████████████████████████████████████████████████████████▏                                                             | 2500/4000 [6:00:58<4:04:42,  9.79s/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 = 2613
+  Batch size = 72
+
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+Configuration saved in ./checkpoint-2500/config.json
+{'eval_loss': 0.4847034215927124, 'eval_wer': 0.39253106771493784, 'eval_runtime': 132.6998, 'eval_samples_per_second': 19.691, 'eval_steps_per_second': 0.279, 'epoch': 62.5}
+Model weights saved in ./checkpoint-2500/pytorch_model.bin
+Configuration saved in ./checkpoint-2500/preprocessor_config.json
+Deleting older checkpoint [checkpoint-2000] due to args.save_total_limit
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+ 65%|███████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                                         | 2600/4000 [6:17:02<2:29:59,  6.43s/it]
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+ 68%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                                     | 2700/4000 [6:31:13<3:35:21,  9.94s/it]
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+ 70%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                                 | 2800/4000 [6:45:03<2:09:33,  6.48s/it]
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+ 72%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                             | 2900/4000 [6:59:16<3:00:07,  9.82s/it]
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+ 75%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                         | 3000/4000 [7:13:03<1:48:27,  6.51s/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 = 2613
+  Batch size = 72
+{'loss': 0.0741, 'learning_rate': 0.00018860610975594382, 'epoch': 75.0}
+
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+100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 37/37 [02:07<00:00,  2.06s/it]
+Configuration saved in ./checkpoint-3000/config.json
+Model weights saved in ./checkpoint-3000/pytorch_model.bin
+Configuration saved in ./checkpoint-3000/preprocessor_config.json
+Deleting older checkpoint [checkpoint-2500] due to args.save_total_limit
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+ 78%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                                     | 3100/4000 [7:29:27<2:29:56, 10.00s/it]
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+ 80%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                 | 3200/4000 [7:43:16<1:27:34,  6.57s/it]
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+ 82%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                             | 3299/4000 [7:57:15<1:42:16,  8.75s/it]
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+ 85%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████��████▏                        | 3399/4000 [8:11:14<1:19:33,  7.94s/it]
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+ 88%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                    | 3500/4000 [8:25:31<1:22:42,  9.93s/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 = 2613
+  Batch size = 72
+{'loss': 0.0608, 'learning_rate': 4.9710474062988955e-05, 'epoch': 87.5}
+
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+100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 37/37 [02:07<00:00,  2.08s/it]
+Configuration saved in ./checkpoint-3500/config.json
+Model weights saved in ./checkpoint-3500/pytorch_model.bin
+Configuration saved in ./checkpoint-3500/preprocessor_config.json
+Deleting older checkpoint [checkpoint-3000] due to args.save_total_limit
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+ 90%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                | 3599/4000 [8:41:30<52:10,  7.81s/it]
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+ 92%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍            | 3700/4000 [8:55:43<49:07,  9.83s/it]
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+ 95%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋        | 3800/4000 [9:09:27<22:19,  6.70s/it]
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+ 98%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊    | 3900/4000 [9:23:35<16:13,  9.74s/it]
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+100%|██████████████████���████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4000/4000 [9:37:22<00:00,  6.61s/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 = 2613
+  Batch size = 72
+{'loss': 0.0541, 'learning_rate': 2.0142048445803695e-10, 'epoch': 100.0}
+
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+100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 37/37 [02:07<00:00,  2.07s/it]
+Configuration saved in ./checkpoint-4000/config.json
+Model weights saved in ./checkpoint-4000/pytorch_model.bin
+Configuration saved in ./checkpoint-4000/preprocessor_config.json
+{'train_runtime': 34778.5805, 'train_samples_per_second': 16.435, 'train_steps_per_second': 0.115, 'train_loss': 0.3524592447280884, 'epoch': 100.0}
+Deleting older checkpoint [checkpoint-3500] due to args.save_total_limit
+Training completed. Do not forget to share your model on huggingface.co/models =)
+100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4000/4000 [9:39:37<00:00,  8.69s/it]
+Saving model checkpoint to ./
+Configuration saved in ./config.json
+Model weights saved in ./pytorch_model.bin
+Configuration saved in ./preprocessor_config.json
+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 = 2613
+  Batch size = 72
+***** train metrics *****
+  epoch                    =      100.0
+  train_loss               =     0.3525
+  train_runtime            = 9:39:38.58
+  train_samples            =       5716
+  train_samples_per_second =     16.435
+  train_steps_per_second   =      0.115
+01/31/2022 23:43:44 - INFO - __main__ - *** Evaluate ***
+
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+100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 37/37 [02:08<00:00,  3.47s/it]
+***** eval metrics *****
+  epoch                   =      100.0
+  eval_loss               =     0.4927
+  eval_runtime            = 0:02:12.07
+  eval_samples            =       2613
+  eval_samples_per_second =     19.785
+  eval_steps_per_second   =       0.28
+  eval_wer                =     0.3536
+Dropping the following result as it does not have all the necessary fields:
+{'dataset': {'name': 'MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - ET', 'type': 'common_voice', 'args': 'Config: et, Training split: train+validation, Eval split: test'}}

wandb/run-20220131_140404-gjg8nz5t/files/requirements.txt

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+
+2022-01-31 23:46:01,500 INFO    MainThread:2738250 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 829187
+  total_bytes: 829187
+}
+
+2022-01-31 23:46:01,602 INFO    MainThread:2738250 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 829187
+  total_bytes: 829187
+}
+
+2022-01-31 23:46:01,704 INFO    MainThread:2738250 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 829187
+  total_bytes: 829187
+}
+
+2022-01-31 23:46:01,807 INFO    MainThread:2738250 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 829187
+  total_bytes: 829187
+}
+
+2022-01-31 23:46:03,074 INFO    MainThread:2738250 [wandb_run.py:_wait_for_finish():1912] got exit ret: file_counts {
+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 829187
+  total_bytes: 829187
+}
+
+2022-01-31 23:46:03,447 INFO    MainThread:2738250 [wandb_run.py:_wait_for_finish():1912] got exit ret: done: true
+exit_result {
+}
+file_counts {
+  wandb_count: 5
+}
+pusher_stats {
+  uploaded_bytes: 829187
+  total_bytes: 829187
+}
+local_info {
+}
+
+2022-01-31 23:46:04,560 INFO    MainThread:2738250 [wandb_run.py:_append_history():2130] rendering history
+2022-01-31 23:46:04,562 INFO    MainThread:2738250 [wandb_run.py:_append_summary():2085] rendering summary
+2022-01-31 23:46:04,563 INFO    MainThread:2738250 [wandb_run.py:_append_files():2180] logging synced files

wandb/run-20220131_140404-gjg8nz5t/run-gjg8nz5t.wandb

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