metadata

tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: fresh-2-layer-medmcqa20000-distill-of-fresh-2-layer-gpqa_EVAL_gpqa
    results: []

fresh-2-layer-medmcqa20000-distill-of-fresh-2-layer-gpqa_EVAL_gpqa

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

Loss: 5.6554
Accuracy: 0.7323

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: 0.0005
train_batch_size: 32
eval_batch_size: 32
seed: 321
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.16	100	15.6094	0.3384
No log	0.32	200	11.2486	0.4747
No log	0.48	300	9.7003	0.5556
No log	0.64	400	9.0128	0.6212
3.508	0.8	500	9.0146	0.6111
3.508	0.96	600	7.8672	0.6465
3.508	1.12	700	7.4123	0.6768
3.508	1.28	800	7.4161	0.6515
3.508	1.44	900	7.3679	0.6667
0.9934	1.6	1000	6.8781	0.6768
0.9934	1.76	1100	6.7447	0.6717
0.9934	1.92	1200	7.6242	0.6818
0.9934	2.08	1300	6.6278	0.6869
0.9934	2.24	1400	6.4569	0.6970
0.6102	2.4	1500	6.7556	0.7121
0.6102	2.56	1600	6.3065	0.7020
0.6102	2.72	1700	6.2906	0.7071
0.6102	2.88	1800	6.2230	0.7121
0.6102	3.04	1900	6.9069	0.7172
0.4278	3.2	2000	6.0706	0.7172
0.4278	3.36	2100	6.0340	0.7172
0.4278	3.52	2200	5.6554	0.7323
0.4278	3.68	2300	5.8829	0.7020
0.4278	3.84	2400	5.6822	0.7222
0.3174	4.0	2500	5.7620	0.7222
0.3174	4.16	2600	5.7952	0.7172
0.3174	4.32	2700	5.6193	0.7222

Framework versions

Transformers 4.34.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.14.0