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

postbot/pythia-160m-hq-emails

pythia-160m-hq-emails-v4