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megachat – AI Model by w95 | AlphaNeural AI
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w95
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megachat
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transformers
pytorch
safetensors
llama
text-generation
generated_from_trainer
TinyLlama/TinyLlama-1.1B-Chat-v0.3
finetune
apache-2.0
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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megachat
This model is a fine-tuned version of
PY007/TinyLlama-1.1B-Chat-v0.3
on an unknown dataset.
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: 0.0002
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
training_steps: 2000
Training results
Framework versions
Transformers 4.34.0
Pytorch 2.1.0+cu121
Datasets 2.14.5
Tokenizers 0.14.1
Open LLM Leaderboard Evaluation Results
Detailed results can be found
here
Metric
Value
Avg.
30.38
ARC (25-shot)
30.8
HellaSwag (10-shot)
54.35
MMLU (5-shot)
25.55
TruthfulQA (0-shot)
39.85
Winogrande (5-shot)
56.99
GSM8K (5-shot)
0.99
DROP (3-shot)
4.16
