metadata
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: pippa-lora
results: []
pippa-lora
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3494
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 40
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.7313 | 0.05 | 100 | 1.7044 |
| 1.68 | 0.11 | 200 | 1.6176 |
| 1.5642 | 0.16 | 300 | 1.5538 |
| 1.6617 | 0.22 | 400 | 1.4986 |
| 1.4733 | 0.27 | 500 | 1.4723 |
| 1.4916 | 0.33 | 600 | 1.4427 |
| 1.5036 | 0.38 | 700 | 1.4271 |
| 1.2385 | 0.44 | 800 | 1.4109 |
| 1.4094 | 0.49 | 900 | 1.3968 |
| 1.4042 | 0.55 | 1000 | 1.3848 |
| 1.3946 | 0.6 | 1100 | 1.3771 |
| 1.2523 | 0.66 | 1200 | 1.3692 |
| 1.2932 | 0.71 | 1300 | 1.3648 |
| 1.346 | 0.77 | 1400 | 1.3609 |
| 1.1163 | 0.82 | 1500 | 1.3565 |
| 1.4656 | 0.88 | 1600 | 1.3495 |
| 1.2698 | 0.93 | 1700 | 1.3484 |
| 1.2019 | 0.99 | 1800 | 1.3454 |
| 1.3685 | 1.04 | 1900 | 1.3477 |
| 1.2248 | 1.1 | 2000 | 1.3488 |
| 1.2162 | 1.15 | 2100 | 1.3479 |
| 1.0443 | 1.21 | 2200 | 1.3491 |
| 1.2445 | 1.26 | 2300 | 1.3460 |
| 1.3229 | 1.32 | 2400 | 1.3476 |
| 1.3464 | 1.37 | 2500 | 1.3439 |
| 1.2651 | 1.43 | 2600 | 1.3439 |
| 1.516 | 1.48 | 2700 | 1.3424 |
| 1.4323 | 1.54 | 2800 | 1.3413 |
| 1.08 | 1.59 | 2900 | 1.3436 |
| 1.289 | 1.64 | 3000 | 1.3379 |
| 1.1221 | 1.7 | 3100 | 1.3384 |
| 1.1895 | 1.75 | 3200 | 1.3376 |
| 1.3138 | 1.81 | 3300 | 1.3358 |
| 1.3907 | 1.86 | 3400 | 1.3343 |
| 1.4544 | 1.92 | 3500 | 1.3351 |
| 1.25 | 1.97 | 3600 | 1.3334 |
| 1.2682 | 2.03 | 3700 | 1.3452 |
| 1.3107 | 2.08 | 3800 | 1.3471 |
| 1.2096 | 2.14 | 3900 | 1.3496 |
| 1.4503 | 2.19 | 4000 | 1.3503 |
| 1.142 | 2.25 | 4100 | 1.3485 |
| 0.8439 | 2.3 | 4200 | 1.3490 |
| 1.2749 | 2.36 | 4300 | 1.3508 |
| 0.9578 | 2.41 | 4400 | 1.3502 |
| 1.2203 | 2.47 | 4500 | 1.3496 |
| 0.9451 | 2.52 | 4600 | 1.3498 |
| 0.9602 | 2.58 | 4700 | 1.3491 |
| 0.9501 | 2.63 | 4800 | 1.3491 |
| 1.2062 | 2.69 | 4900 | 1.3496 |
| 1.1728 | 2.74 | 5000 | 1.3491 |
| 1.2506 | 2.8 | 5100 | 1.3494 |
| 1.4052 | 2.85 | 5200 | 1.3494 |
| 1.2012 | 2.91 | 5300 | 1.3494 |
| 1.3141 | 2.96 | 5400 | 1.3494 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0