t5-base-finetuned-en-to-it-hrs

din0s/t5-base-finetuned-en-to-it-hrs

t5-base-finetuned-en-to-it-hrs is a machine learning model from din0s. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: Oct 9, 2022
Updated: Oct 10, 2022
SHA: 915b5862

Model card

From the Hugging Face model README

t5-base-finetuned-en-to-it-hrs

This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.4678
Bleu: 22.3501
Gen Len: 50.294

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: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 40
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
1.4526	1.0	1125	1.9406	11.7289	57.5773
1.2548	2.0	2250	1.8509	14.9652	53.1013
1.1458	3.0	3375	1.7841	16.7549	52.4607
1.048	4.0	4500	1.7393	18.0223	51.4573
0.9922	5.0	5625	1.6980	18.6182	51.4733
0.9691	6.0	6750	1.6702	19.1118	51.994
0.9382	7.0	7875	1.6493	19.9025	51.128
0.8995	8.0	9000	1.6272	20.2594	51.2807
0.8843	9.0	10125	1.6106	20.4571	50.9607
0.8634	10.0	11250	1.5819	20.6829	51.0007
0.8507	11.0	12375	1.5752	20.6869	51.46
0.824	12.0	13500	1.5612	20.8633	51.2387
0.8124	13.0	14625	1.5496	21.3232	50.684
0.8081	14.0	15750	1.5425	21.4131	50.544
0.7837	15.0	16875	1.5302	21.2258	51.0287
0.7752	16.0	18000	1.5244	21.6548	50.312
0.7698	17.0	19125	1.5197	21.6719	50.7993
0.7606	18.0	20250	1.5168	21.7322	50.5947
0.7527	19.0	21375	1.5128	21.8434	50.4273
0.7515	20.0	22500	1.5008	21.6784	50.4933
0.7436	21.0	23625	1.5010	21.955	50.2093
0.7307	22.0	24750	1.4976	21.9676	50.7
0.7311	23.0	25875	1.4919	22.1018	50.5687
0.7206	24.0	27000	1.4890	22.0666	50.198
0.7142	25.0	28125	1.4843	22.1885	50.312
0.7125	26.0	29250	1.4796	22.1068	50.3167
0.7069	27.0	30375	1.4843	22.2135	50.144
0.701	28.0	31500	1.4761	22.168	50.574
0.6968	29.0	32625	1.4777	22.1219	50.5933
0.704	30.0	33750	1.4745	22.179	50.4773
0.698	31.0	34875	1.4733	22.1779	50.3713
0.6816	32.0	36000	1.4756	22.3355	50.3967
0.681	33.0	37125	1.4713	22.3124	50.192
0.6896	34.0	38250	1.4701	22.2848	50.1133
0.6798	35.0	39375	1.4677	22.2537	50.1573
0.6908	36.0	40500	1.4686	22.2789	50.202
0.6765	37.0	41625	1.4687	22.2854	50.1687
0.679	38.0	42750	1.4675	22.3388	50.3127
0.6788	39.0	43875	1.4672	22.2971	50.2687
0.6744	40.0	45000	1.4678	22.3501	50.294

Framework versions

Transformers 4.22.1
Pytorch 1.12.1
Datasets 2.5.1
Tokenizers 0.11.0

Library: transformers
Type: t5
License: apache-2.0
Created: Oct 9, 2022
Updated: Oct 10, 2022