metadata

license: mit
library_name: peft
tags:
  - generated_from_trainer
base_model: facebook/esm2_t12_35M_UR50D
metrics:
  - accuracy
model-index:
  - name: esm2_t12_35M-lora-binding-sites_2024-04-25_14-35-31
    results: []

esm2_t12_35M-lora-binding-sites_2024-04-25_14-35-31

This model is a fine-tuned version of facebook/esm2_t12_35M_UR50D on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3589
Accuracy: 0.8457

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: 0.0005701568055793089
train_batch_size: 64
eval_batch_size: 64
seed: 8893
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6703	1.0	24	0.6807	0.5820
0.6449	2.0	48	0.6703	0.5820
0.6659	3.0	72	0.6458	0.5977
0.6432	4.0	96	0.6612	0.6328
0.6322	5.0	120	0.6051	0.6523
0.6176	6.0	144	0.6062	0.6504
0.4904	7.0	168	0.5762	0.6777
0.4426	8.0	192	0.5784	0.6953
0.6014	9.0	216	0.5497	0.7148
0.4484	10.0	240	0.5399	0.7227
0.552	11.0	264	0.5142	0.7480
0.3581	12.0	288	0.4395	0.7930
0.3604	13.0	312	0.4201	0.8066
0.2733	14.0	336	0.4107	0.8262
0.2539	15.0	360	0.4373	0.8008
0.3538	16.0	384	0.3954	0.8301
0.4363	17.0	408	0.3852	0.8320
0.3433	18.0	432	0.3735	0.8418
0.2758	19.0	456	0.3685	0.8438
0.2073	20.0	480	0.3860	0.8262
0.3578	21.0	504	0.3689	0.8301
0.3114	22.0	528	0.3626	0.8418
0.3296	23.0	552	0.3621	0.8438
0.276	24.0	576	0.3602	0.8457
0.2583	25.0	600	0.3622	0.8457
0.1917	26.0	624	0.3597	0.8477
0.3588	27.0	648	0.3603	0.8477
0.219	28.0	672	0.3606	0.8438
0.3091	29.0	696	0.3586	0.8457
0.2235	30.0	720	0.3589	0.8457

Framework versions

PEFT 0.10.0
Transformers 4.39.3
Pytorch 2.2.1
Datasets 2.16.1
Tokenizers 0.15.2