gemma-lima – AI Model by pkarypis | AlphaNeural AI

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pkarypis/
gemma-lima

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text-generation

alignment-handbook

generated_from_trainer

google/gemma-7b

autotrain_compatible

text-generation-inference

endpoints_compatible

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gemma-lima

This model is a fine-tuned version of google/gemma-7b on the GAIR/lima dataset. It achieves the following results on the evaluation set:

Loss: 2.7259

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: 2e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 16
gradient_accumulation_steps: 2
total_train_batch_size: 128
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss
10.4256	0.91	5	47.0001
6.0419	2.0	11	43.9691
5.2838	2.91	16	40.7857
4.8705	4.0	22	33.9282
4.196	4.91	27	17.5336
3.0724	6.0	33	2.7088
2.1966	6.91	38	2.7434
2.1116	8.0	44	2.7265
2.0641	8.91	49	2.7168
2.0467	9.09	50	2.7259

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.2