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deadcode99/mistral-billm-token-classification
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metadata
license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: mistral-7b-32k-billm-finetuned-token-classification
    results: []

mistral-7b-32k-billm-finetuned-token-classification

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6070
  • Precision: 0.0
  • Recall: 0.0
  • F1: 0.0
  • Accuracy: 0.7473

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 32
  • 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 Validation Loss Precision Recall F1 Accuracy
No log 0.9957 73 1.0053 0.0 0.0 0.0 0.7275
No log 1.9915 146 0.8578 0.0 0.0 0.0 0.7426
No log 2.9872 219 0.7958 0.0 0.0 0.0 0.7195
No log 3.9966 293 0.6437 0.0 0.0 0.0 0.7144
No log 4.9923 366 0.6283 0.0 0.0 0.0 0.7318
No log 5.9881 439 0.6543 0.0 0.0 0.0 0.7553
0.9335 6.9974 513 0.6112 0.0 0.0 0.0 0.7037
0.9335 7.9932 586 0.6053 0.0 0.0 0.0 0.7373
0.9335 8.9889 659 0.6208 0.0 0.0 0.0 0.7518
0.9335 9.9574 730 0.6070 0.0 0.0 0.0 0.7473

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.1
  • Pytorch 2.2.2
  • Datasets 2.18.0
  • Tokenizers 0.19.1