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pythia-160m-hq-emails-v4

This model is a fine-tuned version of EleutherAI/pythia-160m-deduped on the postbot/multi-emails-hq dataset. It achieves the following results on the evaluation set:

  • Loss: 2.2856
  • Accuracy: 0.6113
  • perplexity: 9.8313

Model description

this is v4

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: 0.0006
  • train_batch_size: 4
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 4.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.412 0.99 76 2.5027 0.5458
1.9702 1.99 152 2.2757 0.5850
1.4628 2.99 228 2.2162 0.6082
1.1662 3.99 304 2.2856 0.6113

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.0
  • Tokenizers 0.13.1

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 25.12
ARC (25-shot) 23.12
HellaSwag (10-shot) 30.05
MMLU (5-shot) 26.58
TruthfulQA (0-shot) 45.51
Winogrande (5-shot) 50.28
GSM8K (5-shot) 0.0
DROP (3-shot) 0.31
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Finetuned from

Space using postbot/pythia-160m-hq-emails 1

Evaluation results