---
library_name: transformers
base_model: MiMe-MeMo/MeMo-BERT-03
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: memo3_indirect_speech
  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. -->

# memo3_indirect_speech

This model is a fine-tuned version of [MiMe-MeMo/MeMo-BERT-03](https://huggingface.co/MiMe-MeMo/MeMo-BERT-03) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.6579
- Precision: 0.6594
- Recall: 0.6579
- F1: 0.6534
- Loss: 0.8215

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1     | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------:|:------:|:------:|:---------------:|
| No log        | 1.0   | 13   | 0.5463   | 0.5179    | 0.5463 | 0.4339 | 1.0286          |
| No log        | 2.0   | 26   | 0.4100   | 0.1876    | 0.4100 | 0.2461 | 1.0251          |
| No log        | 3.0   | 39   | 0.5086   | 0.6698    | 0.5086 | 0.4356 | 0.8710          |
| No log        | 4.0   | 52   | 0.4802   | 0.6966    | 0.4802 | 0.3729 | 1.3227          |
| No log        | 5.0   | 65   | 0.4691   | 0.7161    | 0.4691 | 0.3548 | 1.0735          |
| No log        | 6.0   | 78   | 0.5927   | 0.6874    | 0.5927 | 0.5628 | 0.8102          |
| No log        | 7.0   | 91   | 0.5402   | 0.7032    | 0.5402 | 0.4823 | 1.3396          |
| No log        | 8.0   | 104  | 0.6661   | 0.6753    | 0.6661 | 0.6340 | 0.7542          |
| No log        | 9.0   | 117  | 0.6234   | 0.6935    | 0.6234 | 0.6047 | 0.8814          |
| No log        | 10.0  | 130  | 0.6633   | 0.6732    | 0.6633 | 0.6574 | 0.7494          |
| No log        | 11.0  | 143  | 0.6567   | 0.6597    | 0.6567 | 0.6520 | 0.7748          |
| No log        | 12.0  | 156  | 0.6606   | 0.6596    | 0.6606 | 0.6552 | 0.7600          |
| No log        | 13.0  | 169  | 0.6624   | 0.6744    | 0.6624 | 0.6567 | 0.7976          |
| No log        | 14.0  | 182  | 0.6667   | 0.6668    | 0.6667 | 0.6619 | 0.7685          |
| No log        | 15.0  | 195  | 0.6452   | 0.6778    | 0.6452 | 0.6361 | 0.8573          |
| No log        | 16.0  | 208  | 0.6536   | 0.6721    | 0.6536 | 0.6466 | 0.8498          |
| No log        | 17.0  | 221  | 0.6545   | 0.6625    | 0.6545 | 0.6501 | 0.8457          |
| No log        | 18.0  | 234  | 0.6570   | 0.6602    | 0.6570 | 0.6523 | 0.8187          |
| No log        | 18.48 | 240  | 0.6579   | 0.6594    | 0.6579 | 0.6534 | 0.8215          |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0