Model save

README.md

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+---
+license: apache-2.0
+base_model: zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: 10-finetuned-ausSpiders2000
+  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. -->
+
+# 10-finetuned-ausSpiders2000
+
+This model is a fine-tuned version of [zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000](https://huggingface.co/zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0508
+- Accuracy: 0.9858
+- Precision: 0.9892
+- Recall: 0.9865
+- F1: 0.9878
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.1997        | 1.0   | 281  | 0.2264          | 0.9281   | 0.9395    | 0.8869 | 0.9045 |
+| 0.17          | 2.0   | 563  | 0.1382          | 0.9565   | 0.8540    | 0.8266 | 0.8381 |
+| 0.21          | 3.0   | 845  | 0.1404          | 0.9583   | 0.9747    | 0.9064 | 0.9349 |
+| 0.1976        | 4.0   | 1127 | 0.0987          | 0.9689   | 0.9716    | 0.8917 | 0.9128 |
+| 0.178         | 5.0   | 1408 | 0.1219          | 0.9636   | 0.9393    | 0.9600 | 0.9472 |
+| 0.0659        | 6.0   | 1690 | 0.0804          | 0.9813   | 0.9815    | 0.9801 | 0.9807 |
+| 0.0917        | 7.0   | 1972 | 0.1062          | 0.9734   | 0.9765    | 0.9676 | 0.9716 |
+| 0.108         | 8.0   | 2254 | 0.0568          | 0.9849   | 0.9868    | 0.9794 | 0.9828 |
+| 0.1151        | 9.0   | 2535 | 0.0508          | 0.9858   | 0.9876    | 0.9863 | 0.9869 |
+| 0.049         | 9.97  | 2810 | 0.0508          | 0.9858   | 0.9892    | 0.9865 | 0.9878 |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.13.3

pytorch_model.bin

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