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Llama-2-7b-hf-finetuned-mrpc-v3

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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-v3
    results: []

Llama-2-7b-hf-finetuned-mrpc-v3

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:

  • Loss: 0.6823
  • Accuracy: 0.7475
  • F1: 0.8245

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: 0.0001
  • 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: 40

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.0 230 0.6528 0.625 0.6982
No log 2.0 460 0.6217 0.6936 0.8159
0.6443 3.0 690 0.6033 0.6985 0.7993
0.6443 4.0 920 0.6240 0.6838 0.8089
0.6173 5.0 1150 0.5451 0.7255 0.8170
0.6173 6.0 1380 0.5380 0.7451 0.8188
0.5776 7.0 1610 0.5376 0.7426 0.8346
0.5776 8.0 1840 0.5518 0.7230 0.8243
0.5353 9.0 2070 0.5270 0.7475 0.8325
0.5353 10.0 2300 0.5381 0.7377 0.8086
0.5071 11.0 2530 0.5453 0.7181 0.7842
0.5071 12.0 2760 0.5335 0.7475 0.8341
0.5071 13.0 2990 0.5617 0.7083 0.7733
0.492 14.0 3220 0.5343 0.7426 0.8115
0.492 15.0 3450 0.5133 0.7696 0.8423
0.4608 16.0 3680 0.5573 0.7549 0.8366
0.4608 17.0 3910 0.5282 0.7721 0.8447
0.4283 18.0 4140 0.5894 0.7132 0.7710
0.4283 19.0 4370 0.5875 0.7328 0.8239
0.4042 20.0 4600 0.5447 0.7647 0.8339
0.4042 21.0 4830 0.5712 0.7598 0.8399
0.3904 22.0 5060 0.5563 0.7623 0.8301
0.3904 23.0 5290 0.5718 0.7623 0.8364
0.3597 24.0 5520 0.5592 0.7525 0.8250
0.3597 25.0 5750 0.5941 0.7574 0.8364
0.3597 26.0 5980 0.5811 0.7623 0.8370
0.3445 27.0 6210 0.6083 0.7549 0.8339
0.3445 28.0 6440 0.6049 0.75 0.8265
0.3197 29.0 6670 0.6042 0.7549 0.8311
0.3197 30.0 6900 0.6260 0.7377 0.8099
0.3 31.0 7130 0.6438 0.75 0.8229
0.3 32.0 7360 0.6319 0.7402 0.8233
0.2873 33.0 7590 0.6502 0.7402 0.8191
0.2873 34.0 7820 0.6591 0.7426 0.8187
0.2719 35.0 8050 0.6474 0.7451 0.8219
0.2719 36.0 8280 0.6803 0.7598 0.8367
0.2583 37.0 8510 0.6903 0.7475 0.8221
0.2583 38.0 8740 0.6965 0.7525 0.8279
0.2583 39.0 8970 0.6850 0.75 0.8235
0.2423 40.0 9200 0.6823 0.7475 0.8245

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3