End of training

README.md

@@ -1,15 +1,76 @@
 ---
-license: apache-2.0
-datasets:
-- cy948/ksdoc-airscript
-language:
-- zh
-metrics:
-- accuracy
-base_model:
-- Qwen/Qwen2.5-Coder-1.5B-Instruct
-pipeline_tag: text-generation
 library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
 tags:
-- code
----
+- generated_from_trainer
+model-index:
+- name: Qwen2.5-Coder-1.5B-Instruct-Airscript
+  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. -->
+
+# Qwen2.5-Coder-1.5B-Instruct-Airscript
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2188
+
+## 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: 0.0005
+- train_batch_size: 4
+- eval_batch_size: 4
+- 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: cosine
+- lr_scheduler_warmup_steps: 30
+- training_steps: 1599
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.9398        | 0.0625 | 100  | 1.9159          |
+| 1.6308        | 0.1251 | 200  | 1.6287          |
+| 1.4895        | 0.1876 | 300  | 1.4939          |
+| 1.3812        | 0.2502 | 400  | 1.4127          |
+| 1.316         | 0.3127 | 500  | 1.3550          |
+| 1.2703        | 0.3752 | 600  | 1.3150          |
+| 1.2175        | 0.4378 | 700  | 1.2849          |
+| 1.1885        | 0.5003 | 800  | 1.2648          |
+| 1.1624        | 0.5629 | 900  | 1.2497          |
+| 1.143         | 0.6254 | 1000 | 1.2400          |
+| 1.1334        | 0.6879 | 1100 | 1.2319          |
+| 1.1118        | 0.7505 | 1200 | 1.2259          |
+| 1.1102        | 0.8130 | 1300 | 1.2215          |
+| 1.1017        | 0.8755 | 1400 | 1.2197          |
+| 1.1066        | 0.9381 | 1500 | 1.2188          |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.45.2
+- Pytorch 2.5.0
+- Datasets 3.0.1
+- Tokenizers 0.20.1