End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: finetuning_test
+  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. -->
+
+# finetuning_test
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6970
+- Accuracy: 0.5
+- F1-score: 0.6667
+- Precision: 0.5
+- Recall: 1.0
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 2
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
+| 0.7485        | 0.1   | 1    | 0.6990          | 0.5      | 0.6667   | 0.5       | 1.0    |
+| 0.6785        | 0.2   | 2    | 0.6984          | 0.5      | 0.6667   | 0.5       | 1.0    |
+| 0.6803        | 0.3   | 3    | 0.6982          | 0.5      | 0.6667   | 0.5       | 1.0    |
+| 0.6517        | 0.4   | 4    | 0.6983          | 0.5      | 0.6667   | 0.5       | 1.0    |
+| 0.7254        | 0.5   | 5    | 0.6980          | 0.5      | 0.6667   | 0.5       | 1.0    |
+| 0.6979        | 0.6   | 6    | 0.6978          | 0.5      | 0.6667   | 0.5       | 1.0    |
+| 0.7064        | 0.7   | 7    | 0.6975          | 0.5      | 0.6667   | 0.5       | 1.0    |
+| 0.6709        | 0.8   | 8    | 0.6973          | 0.5      | 0.6667   | 0.5       | 1.0    |
+| 0.7092        | 0.9   | 9    | 0.6971          | 0.5      | 0.6667   | 0.5       | 1.0    |
+| 0.6975        | 1.0   | 10   | 0.6970          | 0.5      | 0.6667   | 0.5       | 1.0    |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 1.0,
+    "total_flos": 1340245973568.0,
+    "train_loss": 0.6966156482696533,
+    "train_runtime": 839.2284,
+    "train_samples_per_second": 0.095,
+    "train_steps_per_second": 0.012
+}

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:de07b6b315d9875b0a229e0a26d7ff3d9142fe95b984e05b46577e821493df08
+oid sha256:dcb1152571af66b6d6a5b59b8e23d13d300e135617b8b615a5365c7c0a72ffb8
 size 737719272

train_results.json

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+{
+    "epoch": 1.0,
+    "total_flos": 1340245973568.0,
+    "train_loss": 0.6966156482696533,
+    "train_runtime": 839.2284,
+    "train_samples_per_second": 0.095,
+    "train_steps_per_second": 0.012
+}