README.md

metadata

license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: scenario-KD-PO-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only55
    results: []

scenario-KD-PO-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only55

This model is a fine-tuned version of haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only on the None dataset. It achieves the following results on the evaluation set:

• Loss: 39.4604
• Accuracy: 0.4537
• F1: 0.4426

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 55
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.72	100	24.2103	0.4616	0.4518
No log	3.45	200	29.3271	0.4255	0.3714
No log	5.17	300	29.8979	0.4489	0.4414
No log	6.9	400	31.7211	0.4669	0.4627
15.3839	8.62	500	37.0421	0.4581	0.4492
15.3839	10.34	600	32.5884	0.4669	0.4658
15.3839	12.07	700	39.9517	0.4493	0.4332
15.3839	13.79	800	38.5249	0.4630	0.4470
15.3839	15.52	900	38.7918	0.4414	0.4286
2.5437	17.24	1000	40.0345	0.4524	0.4391
2.5437	18.97	1100	38.3918	0.4612	0.4527
2.5437	20.69	1200	41.3974	0.4396	0.4169
2.5437	22.41	1300	38.7372	0.4603	0.4532
2.5437	24.14	1400	40.1541	0.4405	0.4288
1.0429	25.86	1500	40.0459	0.4568	0.4383
1.0429	27.59	1600	39.3779	0.4590	0.4457
1.0429	29.31	1700	39.4604	0.4537	0.4426

Framework versions

• Transformers 4.33.3
• Pytorch 2.1.1+cu121
• Datasets 2.14.5
• Tokenizers 0.13.3