metadata

library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
  - generated_from_trainer
datasets:
  - generator
model-index:
  - name: whisper-large-v2-multilingual
    results: []

whisper-large-v2-multilingual

This model is a fine-tuned version of openai/whisper-large-v2 on the generator dataset. It achieves the following results on the evaluation set:

Loss: 0.3502
Wer Eng: 0.01
Wer Lug: 0.106
Wer Ach: 0.241
Wer Lgg: 0.361
Wer Teo: 0.327
Wer Nyn: 0.387
Wer Mean: 0.239
Cer Eng: 0.004
Cer Lug: 0.029
Cer Ach: 0.064
Cer Lgg: 0.118
Cer Teo: 0.145
Cer Nyn: 0.125
Cer Mean: 0.081

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Eng	Wer Lug	Wer Ach	Wer Lgg	Wer Teo	Wer Nyn	Wer Mean	Cer Eng	Cer Lug	Cer Ach	Cer Lgg	Cer Teo	Cer Nyn	Cer Mean
1.0754	0.1	200	0.6042	0.031	0.267	0.428	0.481	0.615	0.712	0.422	0.017	0.053	0.121	0.147	0.242	0.201	0.13
0.5269	1.0001	400	0.4731	0.018	0.176	0.34	0.422	0.45	0.531	0.323	0.008	0.04	0.093	0.126	0.174	0.156	0.099
0.4203	1.1001	600	0.4230	0.018	0.199	0.319	0.416	0.418	0.482	0.309	0.007	0.06	0.094	0.122	0.163	0.146	0.099
0.3851	2.0002	800	0.3871	0.014	0.116	0.271	0.374	0.443	0.454	0.279	0.006	0.03	0.073	0.11	0.19	0.137	0.091
0.3241	2.1002	1000	0.3716	0.015	0.12	0.271	0.392	0.397	0.416	0.269	0.006	0.03	0.077	0.133	0.166	0.127	0.09
0.3161	3.0004	1200	0.3584	0.021	0.121	0.269	0.429	0.36	0.38	0.263	0.008	0.032	0.071	0.154	0.16	0.121	0.091
0.2764	3.1004	1400	0.3546	0.012	0.116	0.254	0.376	0.348	0.403	0.251	0.004	0.03	0.073	0.123	0.155	0.125	0.085
0.2692	4.0005	1600	0.3487	0.011	0.107	0.248	0.352	0.336	0.377	0.238	0.004	0.029	0.067	0.102	0.15	0.123	0.079
0.2427	4.1005	1800	0.3535	0.01	0.113	0.24	0.384	0.329	0.387	0.244	0.004	0.03	0.066	0.122	0.145	0.125	0.082
0.2413	5.0006	2000	0.3502	0.01	0.106	0.241	0.361	0.327	0.387	0.239	0.004	0.029	0.064	0.118	0.145	0.125	0.081

Framework versions

Transformers 4.44.2
Pytorch 2.2.1
Datasets 2.21.0
Tokenizers 0.19.1