byt5-small-cstop_artificial

This model is a fine-tuned version of google/byt5-small on the cstop_artificial dataset. It achieves the following results on the evaluation set:

• Loss: 0.0414
• Exact Match: 0.8283

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: 0.001
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 512
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 3000

Training results

Training Loss	Epoch	Step	Validation Loss	Exact Match
0.2091	25.0	200	0.0555	0.0107
0.0129	50.0	400	0.0414	0.0411
0.004	75.0	600	0.0483	0.0394
0.0018	100.0	800	0.0556	0.0394
0.0011	125.0	1000	0.0598	0.0394
0.0008	150.0	1200	0.0580	0.0376
0.0008	175.0	1400	0.0627	0.0394
0.0005	200.0	1600	0.0658	0.0376
0.0005	225.0	1800	0.0657	0.0376
0.0004	250.0	2000	0.0687	0.0376
0.0003	275.0	2200	0.0731	0.0376
0.0003	300.0	2400	0.0723	0.0376
0.0002	325.0	2600	0.0736	0.0376
0.0002	350.0	2800	0.0741	0.0394
0.0002	375.0	3000	0.0745	0.0394

Framework versions

• Transformers 4.24.0
• Pytorch 1.13.0+cu117
• Datasets 2.7.0
• Tokenizers 0.13.2