README.md

metadata

license: gemma
base_model: google/gemma-2b
tags:
  - generated_from_trainer
model-index:
  - name: G0515HMA9H
    results: []

G0515HMA9H

This model is a fine-tuned version of google/gemma-2b on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1309

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: 0.0003
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine_with_restarts
• lr_scheduler_warmup_steps: 100
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
3.2171	0.09	10	2.8982
2.6882	0.18	20	2.2647
1.8484	0.27	30	1.3286
0.9274	0.36	40	0.4311
0.2813	0.45	50	0.1829
0.1669	0.54	60	0.1548
0.153	0.63	70	0.1492
0.1515	0.73	80	0.1494
0.1428	0.82	90	0.1492
0.1454	0.91	100	0.1488
0.1497	1.0	110	0.1486
0.1434	1.09	120	0.1489
0.145	1.18	130	0.1479
0.1455	1.27	140	0.1470
0.1485	1.36	150	0.1464
0.1421	1.45	160	0.1494
0.1446	1.54	170	0.1463
0.1448	1.63	180	0.1449
0.1462	1.72	190	0.1491
0.1455	1.81	200	0.1469
0.1471	1.9	210	0.1459
0.146	1.99	220	0.1460
0.1423	2.08	230	0.1442
0.136	2.18	240	0.1406
0.1376	2.27	250	0.1414
0.1378	2.36	260	0.1390
0.1353	2.45	270	0.1366
0.1322	2.54	280	0.1349
0.13	2.63	290	0.1321
0.1292	2.72	300	0.1310
0.1317	2.81	310	0.1307
0.1315	2.9	320	0.1309
0.1299	2.99	330	0.1309

Framework versions

• Transformers 4.36.0.dev0
• Pytorch 2.1.2+cu121
• Datasets 2.18.0
• Tokenizers 0.14.1