metadata

base_model: meta-llama/Llama-2-7b-hf
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: Llama-2-7b-hf-finetuned-mrpc
    results: []

Llama-2-7b-hf-finetuned-mrpc

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the glue dataset. It achieves the following results on the evaluation set:

Accuracy: 0.7941
F1: 0.8571
Loss: 0.4479

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Accuracy	F1	Validation Loss
No log	1.0	230	0.7206	0.8155	0.6045
No log	2.0	460	0.6912	0.8158	0.6488
0.6326	3.0	690	0.7279	0.8235	0.5236
0.6326	4.0	920	0.7255	0.8282	0.5273
0.5602	5.0	1150	0.7402	0.8044	0.5246
0.5602	6.0	1380	0.75	0.8311	0.4893
0.5139	7.0	1610	0.7623	0.8289	0.4884
0.5139	8.0	1840	0.7402	0.8307	0.4989
0.4754	9.0	2070	0.7745	0.8435	0.4732
0.4754	10.0	2300	0.7672	0.8403	0.4716
0.5407	11.0	2530	0.7598	0.8393	0.4823
0.5407	12.0	2760	0.7451	0.8333	0.4782
0.5407	13.0	2990	0.7451	0.8333	0.4713
0.4951	14.0	3220	0.7819	0.8489	0.4553
0.4951	15.0	3450	0.7745	0.8506	0.4591
0.4724	16.0	3680	0.7770	0.8423	0.4631
0.4724	17.0	3910	0.8015	0.8576	0.4581
0.4455	18.0	4140	0.7819	0.8468	0.4548
0.4455	19.0	4370	0.7819	0.8484	0.4511
0.4354	20.0	4600	0.7941	0.8571	0.4479

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3