whisper_input_decoder_shift_r_labels_no_force__0035

This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.4228
• Train Accuracy: 0.0308
• Train Wermet: 0.1466
• Validation Loss: 0.8735
• Validation Accuracy: 0.0202
• Validation Wermet: 0.3026
• Epoch: 34

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:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Train Wermet	Validation Loss	Validation Accuracy	Validation Wermet	Epoch
5.6348	0.0091	1.5865	4.2935	0.0093	0.9579	0
4.9212	0.0099	0.9054	4.1262	0.0097	0.9390	1
4.6819	0.0107	0.8319	3.9071	0.0103	0.8966	2
4.4443	0.0114	0.8310	3.7367	0.0106	0.8939	3
4.2479	0.0119	0.8226	3.6101	0.0109	0.8696	4
4.0911	0.0124	0.8103	3.5364	0.0110	0.8946	5
3.9590	0.0127	0.7913	3.4556	0.0113	0.8388	6
3.8513	0.0130	0.7794	3.4106	0.0114	0.8515	7
3.7607	0.0133	0.7657	3.3507	0.0115	0.8261	8
3.6757	0.0136	0.7548	3.3141	0.0116	0.8400	9
3.6023	0.0138	0.7454	3.2711	0.0117	0.8006	10
3.5261	0.0140	0.7348	3.2391	0.0119	0.8101	11
3.4534	0.0143	0.7212	3.2070	0.0120	0.7870	12
3.3814	0.0146	0.7080	3.1505	0.0122	0.7826	13
3.3069	0.0148	0.6961	3.1102	0.0124	0.7609	14
3.2229	0.0152	0.6781	3.0542	0.0125	0.7532	15
3.1334	0.0156	0.6614	2.9840	0.0127	0.7448	16
3.0313	0.0160	0.6425	2.9032	0.0130	0.7123	17
2.9122	0.0166	0.6202	2.7986	0.0134	0.6930	18
2.7559	0.0173	0.5940	2.6337	0.0139	0.6673	19
2.5649	0.0182	0.5674	2.4490	0.0145	0.6383	20
2.3414	0.0193	0.5299	2.2785	0.0150	0.6183	21
2.0966	0.0206	0.4903	2.0460	0.0158	0.5649	22
1.8283	0.0220	0.4459	1.8369	0.0165	0.5306	23
1.5547	0.0235	0.3996	1.6356	0.0172	0.4848	24
1.3218	0.0249	0.3581	1.4682	0.0179	0.4510	25
1.1383	0.0260	0.3211	1.3465	0.0183	0.4226	26
0.9876	0.0270	0.2920	1.2323	0.0188	0.3966	27
0.8635	0.0278	0.2651	1.1482	0.0191	0.3749	28
0.7620	0.0284	0.2435	1.0816	0.0194	0.3565	29
0.6749	0.0290	0.2234	1.0187	0.0196	0.3433	30
0.5998	0.0295	0.2025	0.9761	0.0198	0.3319	31
0.5325	0.0300	0.1827	0.9326	0.0200	0.3213	32
0.4735	0.0305	0.1665	0.8942	0.0201	0.3110	33
0.4228	0.0308	0.1466	0.8735	0.0202	0.3026	34

Framework versions

• Transformers 4.34.0.dev0
• TensorFlow 2.13.0
• Tokenizers 0.13.3