End of training

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: deberta-v3-base-p-tuning-isarcasm
+  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. -->
+
+# deberta-v3-base-p-tuning-isarcasm
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6620
+- Accuracy: 0.4476
+- F1: 0.3603
+- Precision: 0.2266
+- Recall: 0.8790
+
+## 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: 0.001
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 108  | 0.6889          | 0.3143   | 0.2941 | 0.1786    | 0.8333 |
+| No log        | 2.0   | 216  | 0.7020          | 0.8286   | 0.0    | 0.0       | 0.0    |
+| No log        | 3.0   | 324  | 0.6725          | 0.6286   | 0.2353 | 0.1818    | 0.3333 |
+| No log        | 4.0   | 432  | 0.7169          | 0.1714   | 0.2927 | 0.1714    | 1.0    |
+| 0.7087        | 5.0   | 540  | 0.6925          | 0.5429   | 0.3846 | 0.25      | 0.8333 |
+| 0.7087        | 6.0   | 648  | 0.6991          | 0.1714   | 0.2927 | 0.1714    | 1.0    |
+| 0.7087        | 7.0   | 756  | 0.6780          | 0.8286   | 0.0    | 0.0       | 0.0    |
+| 0.7087        | 8.0   | 864  | 0.6851          | 0.8286   | 0.0    | 0.0       | 0.0    |
+| 0.7087        | 9.0   | 972  | 0.6712          | 0.8286   | 0.0    | 0.0       | 0.0    |
+| 0.7055        | 10.0  | 1080 | 0.6767          | 0.3143   | 0.3333 | 0.2       | 1.0    |
+| 0.7055        | 11.0  | 1188 | 0.6720          | 0.5714   | 0.4000 | 0.2632    | 0.8333 |
+| 0.7055        | 12.0  | 1296 | 0.6710          | 0.3714   | 0.3529 | 0.2143    | 1.0    |
+| 0.7055        | 13.0  | 1404 | 0.6676          | 0.4857   | 0.3077 | 0.2       | 0.6667 |
+| 0.6916        | 14.0  | 1512 | 0.6735          | 0.3714   | 0.3125 | 0.1923    | 0.8333 |
+| 0.6916        | 15.0  | 1620 | 0.6762          | 0.3714   | 0.3529 | 0.2143    | 1.0    |
+| 0.6916        | 16.0  | 1728 | 0.6642          | 0.6286   | 0.3158 | 0.2308    | 0.5    |
+| 0.6916        | 17.0  | 1836 | 0.6609          | 0.5143   | 0.32   | 0.2105    | 0.6667 |
+| 0.6916        | 18.0  | 1944 | 0.6632          | 0.4571   | 0.2963 | 0.1905    | 0.6667 |
+| 0.6798        | 19.0  | 2052 | 0.6640          | 0.4      | 0.2759 | 0.1739    | 0.6667 |
+| 0.6798        | 20.0  | 2160 | 0.6644          | 0.4      | 0.2759 | 0.1739    | 0.6667 |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.1.1+cu121
+- Datasets 2.14.5
+- Tokenizers 0.13.3