example | whisper_finetuning Overview – Weights & Biases

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Parambharat's group workspace

Group: example

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Notes

Author

State

Finished

Start time

December 15th, 2022 4:57:39 AM

Runtime

25m 25s

Tracked hours

14m 51s

Run path

parambharat/whisper_finetuning/22b17sfg

OS

Linux-5.15.0-56-generic-x86_64-with-glibc2.35

Python version

3.9.15

Git repository

git clone git@github.com:parambharat/whisper-finetuning.git

Git state

git checkout -b "neat-energy-86" 3785e8c6743f297e70b956d55af3e189fa7d8dbb

Command

notebooks/example_notebook.ipynb

System Hardware

CPU count	10
Logical CPU count	20
GPU count	1
GPU type	NVIDIA GeForce RTX 3060

W&B CLI Version

0.13.6

Group

Job Type

fine-tuning

Config parameters are your model's inputs. Learn more

▶
Config parameters:{} 189 keys
- _name_or_path:
  "parambharat/whisper-tiny-ta"
- activation_dropout:
  0
- activation_function:
  "gelu"
- adafactor:
  false
- adam_beta1:
  0.9
- adam_beta2:
  0.999
- adam_epsilon:
  0.00000001
- add_cross_attention:
  false
- ▶
  architectures:[] 1 item
  - 0:
    "WhisperForConditionalGeneration"
- attention_dropout:
  0
- auto_find_batch_size:
  false
- bad_words_ids:
  null
- ▶
  begin_suppress_tokens:[] 2 items
  - 0:
    220
  - 1:
    50,257
- bf16:
  false
- bf16_full_eval:
  false
- bos_token_id:
  50,257
- chunk_size_feed_forward:
  0
- cross_attention_hidden_size:
  null
- d_model:
  384
- data_seed:
  "None"
- dataloader_drop_last:
  false
- dataloader_num_workers:
  0
- dataloader_pin_memory:
  true
- ddp_bucket_cap_mb:
  "None"
- ddp_find_unused_parameters:
  "None"
- ddp_timeout:
  1,800
- debug:
  "[]"
- decoder_attention_heads:
  6
- decoder_ffn_dim:
  1,536
- decoder_layerdrop:
  0
- decoder_layers:
  4
- decoder_start_token_id:
  50,258
- deepspeed:
  "None"
- disable_tqdm:
  false
- diversity_penalty:
  0
- do_eval:
  true
- do_predict:
  false
- do_sample:
  false
- do_train:
  false
- dropout:
  0
- early_stopping:
  false
- encoder_attention_heads:
  6
- encoder_ffn_dim:
  1,536
- encoder_layerdrop:
  0
- encoder_layers:
  4
- encoder_no_repeat_ngram_size:
  0
- warmup_ratio:
  0
- warmup_steps:
  25
- weight_decay:
  0
- xpu_backend:
  "None"

Summary metrics are your model's outputs. Learn more

▶
Summary metrics:{} 15 keys
- eval/loss:
  0.4016417860984802
- eval/runtime:
  3.4824
- eval/samples_per_second:
  2.872
- eval/steps_per_second:
  0.287
- eval/wer:
  36.52173913043478
- sample_predictions:
  "table-file"
- train/epoch:
  49.02
- train/global_step:
  100
- train/learning_rate:
  0.00000013333333333333
- train/loss:
  0.1096
- train/total_flos:
  123,094,425,600,000,000
- train/train_loss:
  0.19321103930473327
- train/train_runtime:
  666.4579
- train/train_samples_per_second:
  9.603
- train/train_steps_per_second:
  0.15

This run produced these artifacts as outputs. Total: 14. Learn more