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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: Cerebras-GPT-1.3B-lora-s-t3000-v300-v1
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. -->
# Cerebras-GPT-1.3B-lora-s-t3000-v300-v1
This model is a fine-tuned version of [cerebras/Cerebras-GPT-1.3B](https://huggingface.co./cerebras/Cerebras-GPT-1.3B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2409
## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.4608 | 0.11 | 20 | 2.4030 |
| 2.2475 | 0.21 | 40 | 2.2757 |
| 2.2432 | 0.32 | 60 | 2.2579 |
| 2.3011 | 0.43 | 80 | 2.2467 |
| 2.2293 | 0.53 | 100 | 2.2478 |
| 2.1398 | 0.64 | 120 | 2.2436 |
| 2.2571 | 0.75 | 140 | 2.2413 |
| 2.1577 | 0.85 | 160 | 2.2349 |
| 2.2442 | 0.96 | 180 | 2.2371 |
| 2.2592 | 1.07 | 200 | 2.2342 |
| 2.2082 | 1.17 | 220 | 2.2352 |
| 2.1402 | 1.28 | 240 | 2.2345 |
| 2.1216 | 1.39 | 260 | 2.2345 |
| 2.1758 | 1.49 | 280 | 2.2320 |
| 2.1625 | 1.6 | 300 | 2.2329 |
| 2.1491 | 1.71 | 320 | 2.2311 |
| 2.2307 | 1.81 | 340 | 2.2286 |
| 2.1102 | 1.92 | 360 | 2.2300 |
| 2.2054 | 2.03 | 380 | 2.2278 |
| 2.157 | 2.13 | 400 | 2.2345 |
| 2.0643 | 2.24 | 420 | 2.2359 |
| 2.2134 | 2.35 | 440 | 2.2343 |
| 2.1296 | 2.45 | 460 | 2.2347 |
| 2.1001 | 2.56 | 480 | 2.2346 |
| 2.1401 | 2.67 | 500 | 2.2327 |
| 2.091 | 2.77 | 520 | 2.2328 |
| 2.1365 | 2.88 | 540 | 2.2359 |
| 2.1201 | 2.99 | 560 | 2.2295 |
| 2.1359 | 3.09 | 580 | 2.2338 |
| 2.0979 | 3.2 | 600 | 2.2427 |
| 2.2025 | 3.31 | 620 | 2.2345 |
| 2.1001 | 3.41 | 640 | 2.2368 |
| 2.0228 | 3.52 | 660 | 2.2350 |
| 2.1174 | 3.63 | 680 | 2.2362 |
| 2.0688 | 3.73 | 700 | 2.2372 |
| 2.0368 | 3.84 | 720 | 2.2328 |
| 2.1409 | 3.95 | 740 | 2.2341 |
| 2.0675 | 4.05 | 760 | 2.2377 |
| 2.1805 | 4.16 | 780 | 2.2392 |
| 2.0844 | 4.27 | 800 | 2.2417 |
| 2.0834 | 4.37 | 820 | 2.2395 |
| 2.1396 | 4.48 | 840 | 2.2400 |
| 2.1121 | 4.59 | 860 | 2.2394 |
| 2.0195 | 4.69 | 880 | 2.2391 |
| 2.0564 | 4.8 | 900 | 2.2391 |
| 1.9447 | 4.91 | 920 | 2.2396 |
| 2.2122 | 5.01 | 940 | 2.2384 |
| 2.0482 | 5.12 | 960 | 2.2404 |
| 2.051 | 5.23 | 980 | 2.2411 |
| 2.0345 | 5.33 | 1000 | 2.2409 |
### Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2
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