SBIC-google-t5-v1_1-large-intra_model-frequency-model_annots_str

This model is a fine-tuned version of google/t5-v1_1-large on the None dataset. It achieves the following results on the evaluation set:

• Loss: nan

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: 0.0001
• 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: 200

Training results

Training Loss	Epoch	Step	Validation Loss
7.0055	1.0	392	7.4350
5.8944	2.0	784	6.2034
0.5181	3.0	1176	0.4646
0.471	4.0	1568	0.4433
0.4494	5.0	1960	0.4368
0.4886	6.0	2352	0.4374
0.4155	7.0	2744	0.4516
0.4407	8.0	3136	0.4304
0.4527	9.0	3528	0.4213
0.428	10.0	3920	0.4149
0.4312	11.0	4312	0.4148
0.4167	12.0	4704	0.4128
0.4474	13.0	5096	0.4140
0.4238	14.0	5488	0.4100
0.423	15.0	5880	0.4096
0.4319	16.0	6272	0.4085
0.4267	17.0	6664	0.4067
0.4568	18.0	7056	0.4058
0.4426	19.0	7448	0.4059
0.3938	20.0	7840	0.4042
0.4136	21.0	8232	0.4053
0.421	22.0	8624	0.4040
0.4043	23.0	9016	0.4050
0.4159	24.0	9408	0.4046
0.401	25.0	9800	0.4040
0.4128	26.0	10192	0.4039
0.4123	27.0	10584	0.4039
0.4089	28.0	10976	0.4039
0.4346	29.0	11368	0.4039
0.437	30.0	11760	0.4039
0.4077	31.0	12152	0.4039

Framework versions

• Transformers 4.34.0
• Pytorch 2.1.0+cu121
• Datasets 2.14.5
• Tokenizers 0.14.1