---
library_name: transformers
base_model: spear-model/mbert-kmeans-0.05.mmarco.L-all-en.S-all.30K
tags:
- generated_from_trainer
model-index:
- name: mbert-kmeans-0.05.mmarco.L-all-en.S-all.30K.distill-test.mt5-base-mmarco-v2.30K
  results: []
---

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# mbert-kmeans-0.05.mmarco.L-all-en.S-all.30K.distill-test.mt5-base-mmarco-v2.30K

This model is a fine-tuned version of [spear-model/mbert-kmeans-0.05.mmarco.L-all-en.S-all.30K](https://huggingface.co/spear-model/mbert-kmeans-0.05.mmarco.L-all-en.S-all.30K) on an unknown dataset.

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 30000

### Training results



### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0