Downloads · 30 days
22
18% of all-time downloads
deepseek-llm-7b-base-2-contract-sections-classification-v4
marcelovidigal/deepseek-llm-7b-base-2-contract-sections-classification-v4
deepseek-llm-7b-base-2-contract-sections-classification-v4 is a machine learning model from marcelovidigal. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
All-time downloads
121
Public
Repo size
110 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors15.7 MB · 68%
At a glance
- Library
- peft
- License
- other
- Access
- Public
- Created
- Feb 21, 2025
- Updated
- Feb 24, 2025
- SHA
- 0f8bb548
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>
deepseek-llm-7b-base-2-contract-sections-classification-v4
This model is a fine-tuned version of deepseek-ai/deepseek-llm-7b-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6235
- Accuracy Evaluate: 0.13
- Precision Evaluate: 0.0501
- Recall Evaluate: 0.0633
- F1 Evaluate: 0.0303
- Accuracy Sklearn: 0.13
- Precision Sklearn: 0.0410
- Recall Sklearn: 0.13
- F1 Sklearn: 0.0475
- Acuracia Rotulo Objeto: 0.0
- Acuracia Rotulo Obrigacoes: 0.7391
- Acuracia Rotulo Valor: 0.0
- Acuracia Rotulo Vigencia: 0.0
- Acuracia Rotulo Rescisao: 0.0
- Acuracia Rotulo Foro: 0.0
- Acuracia Rotulo Reajuste: 0.0
- Acuracia Rotulo Fiscalizacao: 0.0
- Acuracia Rotulo Publicacao: 0.0
- Acuracia Rotulo Pagamento: 0.0
- Acuracia Rotulo Casos Omissos: 0.0
- Acuracia Rotulo Sancoes: 0.0833
- Acuracia Rotulo Dotacao Orcamentaria: 0.0
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: 1e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Evaluate | Precision Evaluate | Recall Evaluate | F1 Evaluate | Accuracy Sklearn | Precision Sklearn | Recall Sklearn | F1 Sklearn | Acuracia Rotulo Objeto | Acuracia Rotulo Obrigacoes | Acuracia Rotulo Valor | Acuracia Rotulo Vigencia | Acuracia Rotulo Rescisao | Acuracia Rotulo Foro | Acuracia Rotulo Reajuste | Acuracia Rotulo Fiscalizacao | Acuracia Rotulo Publicacao | Acuracia Rotulo Pagamento | Acuracia Rotulo Casos Omissos | Acuracia Rotulo Sancoes | Acuracia Rotulo Dotacao Orcamentaria |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 125 | 2.6317 | 0.13 | 0.0502 | 0.0633 | 0.0305 | 0.13 | 0.0413 | 0.13 | 0.0479 | 0.0 | 0.7391 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0 |
| No log | 2.0 | 250 | 2.6288 | 0.13 | 0.0502 | 0.0633 | 0.0304 | 0.13 | 0.0413 | 0.13 | 0.0478 | 0.0 | 0.7391 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0 |
| No log | 3.0 | 375 | 2.6261 | 0.13 | 0.0501 | 0.0633 | 0.0303 | 0.13 | 0.0411 | 0.13 | 0.0476 | 0.0 | 0.7391 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0 |
| 2.6801 | 4.0 | 500 | 2.6242 | 0.13 | 0.0501 | 0.0633 | 0.0304 | 0.13 | 0.0412 | 0.13 | 0.0477 | 0.0 | 0.7391 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0 |
| 2.6801 | 5.0 | 625 | 2.6235 | 0.13 | 0.0501 | 0.0633 | 0.0303 | 0.13 | 0.0410 | 0.13 | 0.0475 | 0.0 | 0.7391 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0
- Library
- peft
- License
- other
- Created
- Feb 21, 2025
- Updated
- Feb 24, 2025