End of training

README.md

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+---
+license: apache-2.0
+base_model: ltg/norbert3-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: norbert3-large-user-needs-v2
+  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. -->
+
+# norbert3-large-user-needs-v2
+
+This model is a fine-tuned version of [ltg/norbert3-large](https://huggingface.co/ltg/norbert3-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.1392
+- Accuracy: 0.7067
+- F1: 0.6946
+- Precision: 0.6905
+- Recall: 0.7067
+
+## 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: 3e-05
+- train_batch_size: 4
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 375  | 0.8059          | 0.6747   | 0.6472 | 0.6569    | 0.6747 |
+| 0.9129        | 2.0   | 750  | 0.9030          | 0.6453   | 0.6142 | 0.5975    | 0.6453 |
+| 0.7636        | 3.0   | 1125 | 0.7755          | 0.6667   | 0.6292 | 0.6250    | 0.6667 |
+| 0.6003        | 4.0   | 1500 | 1.0267          | 0.6773   | 0.6591 | 0.6928    | 0.6773 |
+| 0.6003        | 5.0   | 1875 | 1.9897          | 0.6267   | 0.6378 | 0.6526    | 0.6267 |
+| 0.2905        | 6.0   | 2250 | 2.0507          | 0.704    | 0.6913 | 0.6879    | 0.704  |
+| 0.0901        | 7.0   | 2625 | 2.7638          | 0.6853   | 0.6590 | 0.6863    | 0.6853 |
+| 0.0365        | 8.0   | 3000 | 2.6138          | 0.696    | 0.6875 | 0.6907    | 0.696  |
+| 0.0365        | 9.0   | 3375 | 3.0024          | 0.6667   | 0.6585 | 0.6543    | 0.6667 |
+| 0.0162        | 10.0  | 3750 | 2.9416          | 0.6933   | 0.6829 | 0.6798    | 0.6933 |
+| 0.0022        | 11.0  | 4125 | 3.2015          | 0.6827   | 0.6558 | 0.6790    | 0.6827 |
+| 0.0114        | 12.0  | 4500 | 3.3133          | 0.6933   | 0.6694 | 0.6916    | 0.6933 |
+| 0.0114        | 13.0  | 4875 | 3.2376          | 0.6773   | 0.6695 | 0.6647    | 0.6773 |
+| 0.0042        | 14.0  | 5250 | 3.1392          | 0.7067   | 0.6946 | 0.6905    | 0.7067 |
+| 0.0035        | 15.0  | 5625 | 3.2710          | 0.6907   | 0.6770 | 0.6705    | 0.6907 |
+| 0.0045        | 16.0  | 6000 | 3.3476          | 0.6933   | 0.6847 | 0.6841    | 0.6933 |
+| 0.0045        | 17.0  | 6375 | 3.2386          | 0.696    | 0.6904 | 0.6932    | 0.696  |
+| 0.0065        | 18.0  | 6750 | 3.4263          | 0.6853   | 0.6700 | 0.6607    | 0.6853 |
+| 0.0029        | 19.0  | 7125 | 3.4898          | 0.6827   | 0.6652 | 0.6579    | 0.6827 |
+| 0.0013        | 20.0  | 7500 | 3.5103          | 0.68     | 0.6624 | 0.6554    | 0.68   |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.1.0
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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