File size: 3,047 Bytes
85d60dc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0515HMA9H
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# G0515HMA9H
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co./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
|