TestZee/t5-small-finetuned-kaggle-data-t5-v3.0

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 1.6248
• Validation Loss: 1.6558
• Train Rouge1: 26.3006
• Train Rouge2: 15.0931
• Train Rougel: 22.7561
• Train Rougelsum: 24.3816
• Train Gen Len: 19.0
• Epoch: 29

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': 0.001}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Rouge1	Train Rouge2	Train Rougel	Train Rougelsum	Train Gen Len	Epoch
2.1318	1.8436	24.0637	12.9655	20.6308	22.1857	19.0	0
2.0035	1.7955	24.9502	13.7602	21.4422	23.0424	19.0	1
1.9561	1.7670	25.6590	14.5211	22.0967	23.5134	19.0	2
1.9227	1.7496	25.8863	14.7209	22.3661	23.8629	19.0	3
1.8951	1.7334	26.0026	14.7861	22.4126	23.8936	19.0	4
1.8716	1.7234	26.3796	14.9421	22.7097	24.2118	19.0	5
1.8558	1.7138	26.2830	14.9347	22.8008	24.1908	19.0	6
1.8362	1.7072	26.0811	14.6698	22.5673	23.9941	19.0	7
1.8222	1.7020	26.0600	14.8445	22.6614	23.9462	19.0	8
1.8086	1.6929	26.3903	15.0590	22.9725	24.3007	19.0	9
1.7958	1.6870	26.2563	14.8773	22.7601	24.1487	19.0	10
1.7802	1.6847	26.2638	15.0330	22.8279	24.2225	19.0	11
1.7709	1.6823	26.0351	14.9826	22.6653	24.0415	19.0	12
1.7610	1.6796	26.1864	15.0833	22.7959	24.1713	19.0	13
1.7486	1.6754	26.2693	15.2384	22.8580	24.2483	19.0	14
1.7354	1.6744	26.1257	14.9953	22.7029	24.0956	19.0	15
1.7262	1.6740	26.1954	15.0393	22.8311	24.1282	19.0	16
1.7206	1.6703	26.1409	14.9949	22.7586	24.1355	19.0	17
1.7083	1.6663	26.1880	15.1119	22.7500	24.1816	19.0	18
1.7002	1.6662	25.9666	14.9556	22.5439	23.9713	19.0	19
1.6926	1.6654	26.1649	15.1911	22.8287	24.2002	19.0	20
1.6839	1.6589	26.2105	15.0021	22.7778	24.2852	19.0	21
1.6768	1.6596	26.1263	14.8676	22.6634	24.1171	19.0	22
1.6670	1.6612	25.9718	14.8101	22.5048	23.9592	19.0	23
1.6604	1.6590	26.2419	15.0633	22.7685	24.3165	19.0	24
1.6498	1.6564	26.2757	15.0082	22.8157	24.3126	19.0	25
1.6455	1.6570	26.2307	14.9338	22.6259	24.2636	19.0	26
1.6368	1.6573	26.4114	15.3485	22.9117	24.4928	19.0	27
1.6325	1.6547	26.5272	15.4393	23.0764	24.6935	19.0	28
1.6248	1.6558	26.3006	15.0931	22.7561	24.3816	19.0	29

Framework versions

• Transformers 4.20.1
• TensorFlow 2.8.2
• Datasets 2.3.2
• Tokenizers 0.12.1