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Model: formalmathatepfl/deepseek-prover-v2-cpt-sft-feedback-1e
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: other
+base_model: deepseek-ai/DeepSeek-Prover-V2-7B
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: deepseek-prover-v2-7b-lean-cpt-sft-feedback-32k
+  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. -->
+
+# deepseek-prover-v2-7b-lean-cpt-sft-feedback-32k
+
+This model is a fine-tuned version of [deepseek-ai/DeepSeek-Prover-V2-7B](https://huggingface.co/deepseek-ai/DeepSeek-Prover-V2-7B) on the lean_sft_feedback dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0217
+
+## 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-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 16
+- total_eval_batch_size: 16
+- 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: cosine
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss |
+|:-------------:|:------:|:-----:|:---------------:|
+| 0.0399        | 0.0827 | 1000  | 0.0343          |
+| 0.0261        | 0.1654 | 2000  | 0.0284          |
+| 0.0283        | 0.2481 | 3000  | 0.0264          |
+| 0.0228        | 0.3308 | 4000  | 0.0250          |
+| 0.0215        | 0.4135 | 5000  | 0.0242          |
+| 0.0216        | 0.4962 | 6000  | 0.0235          |
+| 0.0228        | 0.5789 | 7000  | 0.0229          |
+| 0.0214        | 0.6616 | 8000  | 0.0225          |
+| 0.0232        | 0.7444 | 9000  | 0.0221          |
+| 0.0205        | 0.8271 | 10000 | 0.0219          |
+| 0.0214        | 0.9098 | 11000 | 0.0218          |
+| 0.0241        | 0.9925 | 12000 | 0.0217          |
+
+
+### Framework versions
+
+- Transformers 4.57.3
+- Pytorch 2.9.0+cu129
+- Datasets 3.6.0
+- Tokenizers 0.22.1