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# my_awesome_model

This model is a fine-tuned version of [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3051
- Accuracy: 0.5429

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 17   | 1.9177          | 0.2714   |
| No log        | 2.0   | 34   | 1.6103          | 0.5143   |
| No log        | 3.0   | 51   | 1.4449          | 0.4857   |
| No log        | 4.0   | 68   | 1.3059          | 0.5714   |
| No log        | 5.0   | 85   | 1.1685          | 0.6      |
| No log        | 6.0   | 102  | 1.2066          | 0.5857   |
| No log        | 7.0   | 119  | 1.2279          | 0.5429   |
| No log        | 8.0   | 136  | 1.2694          | 0.5429   |
| No log        | 9.0   | 153  | 1.3155          | 0.5571   |
| No log        | 10.0  | 170  | 1.3051          | 0.5429   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "intfloat/multilingual-e5-large", "model-index": [{"name": "my_awesome_model", "results": []}]}
transformers tensorboard safetensors xlm-roberta text-classification generated_from_trainer base_model:intfloat/multilingual-e5-large license:mit autotrain_compatible endpoints_compatible region:us