Hi everyone,Opening this thread to discuss about or collaborate on fine-tuning XLSR-Wav2Vec2 for Kyrgyz.
2021-03-26T04:09:30Z
Results of the first run:{“epoch”: 30.0,“eval_loss”: 0.4920000433921814,“eval_mem_cpu_alloc_delta”: 118951837,“eval_mem_cpu_peaked_delta”: 44984344,“eval_mem_gpu_alloc_delta”: 0,“eval_mem_gpu_peaked_delta”: 6326542848,“eval_runtime”: 145.0179,“eval_samples”: 1503,“eval_samples_per_second”: 10.364,“eval_wer”: 0.5470570952893938,“init_mem_cpu_alloc_delta”: 10150057,“init_mem_cpu_peaked_delta”: 18306,“init_mem_gpu_alloc_delta”: 1261919232,“init_mem_gpu_peaked_delta”: 0,“train_mem_cpu_alloc_delta”: 2815161,“train_mem_cpu_peaked_delta”: 300144618,“train_mem_gpu_alloc_delta”: 3787529728,“train_mem_gpu_peaked_delta”: 14746535424,“train_runtime”: 13357.7567,“train_samples”: 3466,“train_samples_per_second”: 0.245}I forgot to remove " character in the preprocessing stage. I’ll try to remove it and run it again.Hyperparams were the same as in Turkish.
2021-03-29T06:27:27Z
My attempts are failing except the very first one.Screen Shot 2021-03-29 at 12.23.132170×698 154 KBThe first run went seemingly well, but I ended up with an empty fileScreen Shot 2021-03-29 at 12.24.552256×88 9.99 KBI’ll try to remove the object storage instance and start all over again.P.S. The last run’s WER score was about ~0.45 with the following params:#!/usr/bin/env bashpython run_common_voice.py–model_name_or_path=“facebook/wav2vec2-large-xlsr-53”–dataset_config_name=“ky”–output_dir=/workspace/output_models/ky6/wav2vec2-large-xlsr-kyrgyz-demo–cache_dir=/workspace/data/ky–overwrite_output_dir–num_train_epochs=“15”–per_device_train_batch_size=“16”–per_device_eval_batch_size=“16”–evaluation_strategy=“steps”–learning_rate=“2.34e-4”–warmup_steps=“500”–fp16–freeze_feature_extractor–save_steps=“1000”–eval_steps=“1000”–save_total_limit=“2”–dataloader_num_workers=“8”–logging_steps=“4000”–group_by_length–feat_proj_dropout=“0.0”–attention_dropout=“0.094”–activation_dropout=“0.055”–hidden_dropout=“0.047”–feat_proj_dropout=“0.04”–mask_time_prob=“0.0082”–layerdrop=“0.041”–gradient_checkpointing–do_train --do_evalThis is the code I ran in OVH:GitHubGitHub - jqueguiner/wav2vec2-sprint: docker for HF wav2vec2-sprintdocker for HF wav2vec2-sprint. Contribute to jqueguiner/wav2vec2-sprint development by creating an account on GitHub.The params given above were applied infinetune.sh
2021-03-29T08:11:22Z
Cleaning up Object storage really worked! Results are like this:wandb: Waiting for W&B process to finish, PID 237wandb: Program ended successfully.wandb:wandb: Find user logs for this run at: /workspace/wav2vec/wandb/run-20210329_070950-1smhj63f/logs/debug.logwandb: Find internal logs for this run at: /workspace/wav2vec/wandb/run-20210329_070950-1smhj63f/logs/debug-internal.logwandb: Run summary:wandb:                        eval/loss 0.47827wandb:eval/wer 0.48556wandb:                     eval/runtime 41.7707wandb:          eval/samples_per_second 35.982wandb:                      train/epoch 15.0wandb:                train/global_step 3255wandb:                            _step 4wandb:                         _runtime 3367wandb:                       _timestamp 1617005157wandb:              train/train_runtime 3461.6067wandb:   train/train_samples_per_second 0.94wandb:                 train/total_flos 7.8449973088273e+18wandb: Run history:wandb:                        eval/loss █▁▁▁wandb:                         eval/wer █▃▁▁wandb:                     eval/runtime █▇▁▂wandb:          eval/samples_per_second ▁▂█▇wandb:                      train/epoch ▁▄▇██Screen Shot 2021-03-29 at 14.14.17868×608 17.6 KB
2021-10-21T16:40:56Z
hi@muratnow you can continue fine tuning using this notebook and repocolab.research.google.comGoogle Colaboratorygithub.comtransformers/examples/pytorch/speech-recognition at main ·...main/examples/pytorch/speech-recognition🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - transformers/examples/pytorch/speech-recognition at main · huggingface/transformers