Model save

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: 1_microsoft_deberta_V1.0
+  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. -->
+
+# 1_microsoft_deberta_V1.0
+
+This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1558
+- Map@3: 0.7650
+- Accuracy: 0.655
+
+## 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: 2e-05
+- train_batch_size: 2
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 25
+- total_train_batch_size: 50
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 60
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Map@3  | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
+| 1.6051        | 0.01  | 10   | 1.6088          | 0.6350 | 0.515    |
+| 1.6082        | 0.02  | 20   | 1.5999          | 0.7192 | 0.595    |
+| 1.5893        | 0.03  | 30   | 1.5422          | 0.7417 | 0.63     |
+| 1.4097        | 0.03  | 40   | 1.2963          | 0.7400 | 0.62     |
+| 1.2099        | 0.04  | 50   | 1.1738          | 0.7608 | 0.645    |
+| 1.1201        | 0.05  | 60   | 1.1558          | 0.7650 | 0.655    |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.0
+- Datasets 2.9.0
+- Tokenizers 0.13.3