lora_alpha_64_drop_0.3_rank_32_seed_42_merges_20_07062024

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

• Loss: 0.4543
• Accuracy: 0.8329

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: 0.0003
• 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: 25.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3479	1.0	12272	0.4573	0.8273
0.3469	2.0	24544	0.4800	0.8265
0.3422	3.0	36816	0.4647	0.8309
0.3461	4.0	49088	0.4541	0.8382
0.3461	5.0	61360	0.4645	0.8357
0.3477	6.0	73632	0.4609	0.8386
0.33	7.0	85904	0.4655	0.8321
0.3483	8.0	98176	0.4539	0.8337
0.3471	9.0	110448	0.4707	0.8333
0.3384	10.0	122720	0.4505	0.8349
0.3385	11.0	134992	0.4598	0.8321
0.334	12.0	147264	0.4544	0.8369
0.3362	13.0	159536	0.4711	0.8289
0.3289	14.0	171808	0.4561	0.8309
0.3334	15.0	184080	0.4773	0.8297
0.3347	16.0	196352	0.4567	0.8345
0.3469	17.0	208624	0.4627	0.8333
0.3425	18.0	220896	0.4622	0.8337
0.3365	19.0	233168	0.4579	0.8337
0.3456	20.0	245440	0.4676	0.8325
0.3398	21.0	257712	0.4538	0.8349
0.3474	22.0	269984	0.4540	0.8333
0.3455	23.0	282256	0.4534	0.8341
0.346	24.0	294528	0.4583	0.8325
0.3428	25.0	306800	0.4543	0.8329

Framework versions

• PEFT 0.11.1
• Transformers 4.41.1
• Pytorch 2.3.0+cu121
• Datasets 2.18.0
• Tokenizers 0.19.1