Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: intfloat/e5-base-v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: e5-base-v2-sentiment-twitter
+  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. -->
+
+# e5-base-v2-sentiment-twitter
+
+This model is a fine-tuned version of [intfloat/e5-base-v2](https://huggingface.co/intfloat/e5-base-v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6678
+- Accuracy: 0.7186
+- F1: 0.7186
+- Precision: 0.7219
+- Recall: 0.7186
+
+## 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: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6842        | 0.1754 | 500  | 0.6403          | 0.7195   | 0.7209 | 0.7232    | 0.7195 |
+| 0.6395        | 0.3508 | 1000 | 0.6110          | 0.7215   | 0.7254 | 0.7374    | 0.7215 |
+| 0.6188        | 0.5261 | 1500 | 0.6028          | 0.733    | 0.7360 | 0.7442    | 0.733  |
+| 0.6291        | 0.7015 | 2000 | 0.5912          | 0.738    | 0.7338 | 0.7403    | 0.738  |
+| 0.6005        | 0.8769 | 2500 | 0.5705          | 0.752    | 0.7534 | 0.7572    | 0.752  |
+| 0.3942        | 1.0523 | 3000 | 0.6278          | 0.747    | 0.7469 | 0.7525    | 0.747  |
+| 0.4603        | 1.2276 | 3500 | 0.6185          | 0.75     | 0.7509 | 0.7536    | 0.75   |
+| 0.4579        | 1.4030 | 4000 | 0.6348          | 0.751    | 0.7491 | 0.7526    | 0.751  |
+| 0.4264        | 1.5784 | 4500 | 0.6129          | 0.757    | 0.7573 | 0.7579    | 0.757  |
+| 0.4196        | 1.7538 | 5000 | 0.6196          | 0.7585   | 0.7582 | 0.7582    | 0.7585 |
+| 0.4193        | 1.9291 | 5500 | 0.6159          | 0.7625   | 0.7611 | 0.7615    | 0.7625 |
+
+
+### Framework versions
+
+- Transformers 4.55.4
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.4

all_results.json

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+{
+    "epoch": 2.0,
+    "eval_accuracy": 0.7185770107456855,
+    "eval_f1": 0.7186205105648833,
+    "eval_loss": 0.6678091287612915,
+    "eval_precision": 0.7219022999609779,
+    "eval_recall": 0.7185770107456855,
+    "eval_runtime": 20.1293,
+    "eval_samples_per_second": 610.256,
+    "eval_steps_per_second": 19.077
+}

model.safetensors

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 version https://git-lfs.github.com/spec/v1
-oid sha256:0c7234e88901a840ce2e3c6486e41d7cc4c9f1b1d894c32023944fb70a394ec4
+oid sha256:77ed2f1ab508a167282439eeb9c077b61b3165aa3ad947c77d691e31d3682dfc
 size 437961724

test_results.json

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+{
+    "epoch": 2.0,
+    "eval_accuracy": 0.7185770107456855,
+    "eval_f1": 0.7186205105648833,
+    "eval_loss": 0.6678091287612915,
+    "eval_precision": 0.7219022999609779,
+    "eval_recall": 0.7185770107456855,
+    "eval_runtime": 20.1293,
+    "eval_samples_per_second": 610.256,
+    "eval_steps_per_second": 19.077
+}