End of training

README.md

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+---
+license: cc-by-nc-4.0
+base_model: MCG-NJU/videomae-base-finetuned-kinetics
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: videomae-base-finetuned-kinetics-fight_18-03-2024
+  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. -->
+
+# videomae-base-finetuned-kinetics-fight_18-03-2024
+
+This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2211
+- Accuracy: 0.9175
+- Precision: 0.9372
+- Recall: 0.895
+
+## 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: 5e-07
+- train_batch_size: 12
+- eval_batch_size: 12
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 2660
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
+| 0.7318        | 0.05  | 134  | 0.7169          | 0.43     | 0.4247    | 0.395  |
+| 0.6646        | 1.05  | 268  | 0.6636          | 0.59     | 0.6139    | 0.485  |
+| 0.6089        | 2.05  | 402  | 0.5944          | 0.78     | 0.8415    | 0.69   |
+| 0.5485        | 3.05  | 536  | 0.5270          | 0.845    | 0.8920    | 0.785  |
+| 0.4581        | 4.05  | 670  | 0.4630          | 0.865    | 0.9011    | 0.82   |
+| 0.3436        | 5.05  | 804  | 0.3994          | 0.8725   | 0.9162    | 0.82   |
+| 0.3109        | 6.05  | 938  | 0.3530          | 0.8775   | 0.9171    | 0.83   |
+| 0.2672        | 7.05  | 1072 | 0.3212          | 0.88     | 0.9176    | 0.835  |
+| 0.2243        | 8.05  | 1206 | 0.2947          | 0.895    | 0.9202    | 0.865  |
+| 0.297         | 9.05  | 1340 | 0.2779          | 0.895    | 0.9202    | 0.865  |
+| 0.21          | 10.05 | 1474 | 0.2615          | 0.9025   | 0.9215    | 0.88   |
+| 0.2003        | 11.05 | 1608 | 0.2515          | 0.895    | 0.9202    | 0.865  |
+| 0.2128        | 12.05 | 1742 | 0.2418          | 0.91     | 0.9271    | 0.89   |
+| 0.1789        | 13.05 | 1876 | 0.2357          | 0.9125   | 0.9275    | 0.895  |
+| 0.1672        | 14.05 | 2010 | 0.2300          | 0.91     | 0.9227    | 0.895  |
+| 0.1532        | 15.05 | 2144 | 0.2275          | 0.9175   | 0.9372    | 0.895  |
+| 0.1695        | 16.05 | 2278 | 0.2241          | 0.9125   | 0.9275    | 0.895  |
+| 0.1255        | 17.05 | 2412 | 0.2225          | 0.915    | 0.9323    | 0.895  |
+| 0.1168        | 18.05 | 2546 | 0.2214          | 0.9175   | 0.9372    | 0.895  |
+| 0.1395        | 19.04 | 2660 | 0.2211          | 0.9175   | 0.9372    | 0.895  |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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 size 344937328