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---
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
model-index:
- name: G0519ABLATION1V1
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. -->
# G0519ABLATION1V1
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: 0.1220
## 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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2296 | 0.09 | 10 | 2.9618 |
| 2.6424 | 0.18 | 20 | 2.1739 |
| 1.7328 | 0.27 | 30 | 1.1890 |
| 0.7887 | 0.36 | 40 | 0.3608 |
| 0.233 | 0.45 | 50 | 0.1685 |
| 0.1612 | 0.54 | 60 | 0.1533 |
| 0.1514 | 0.63 | 70 | 0.1494 |
| 0.1517 | 0.73 | 80 | 0.1488 |
| 0.142 | 0.82 | 90 | 0.1491 |
| 0.1459 | 0.91 | 100 | 0.1478 |
| 0.1487 | 1.0 | 110 | 0.1481 |
| 0.1431 | 1.09 | 120 | 0.1477 |
| 0.1443 | 1.18 | 130 | 0.1467 |
| 0.1448 | 1.27 | 140 | 0.1453 |
| 0.1465 | 1.36 | 150 | 0.1442 |
| 0.1404 | 1.45 | 160 | 0.1448 |
| 0.1428 | 1.54 | 170 | 0.1444 |
| 0.1424 | 1.63 | 180 | 0.1405 |
| 0.1421 | 1.72 | 190 | 0.1413 |
| 0.1371 | 1.81 | 200 | 0.1390 |
| 0.1376 | 1.9 | 210 | 0.1339 |
| 0.1351 | 1.99 | 220 | 0.1293 |
| 0.1296 | 2.08 | 230 | 0.1285 |
| 0.1277 | 2.18 | 240 | 0.1271 |
| 0.1269 | 2.27 | 250 | 0.1276 |
| 0.1286 | 2.36 | 260 | 0.1252 |
| 0.1283 | 2.45 | 270 | 0.1267 |
| 0.1244 | 2.54 | 280 | 0.1252 |
| 0.1213 | 2.63 | 290 | 0.1230 |
| 0.12 | 2.72 | 300 | 0.1220 |
| 0.1263 | 2.81 | 310 | 0.1219 |
| 0.1238 | 2.9 | 320 | 0.1220 |
| 0.1256 | 2.99 | 330 | 0.1220 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
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