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---
language:
- fi
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- fi
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: XLS-R-300M - Finnish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: fi
metrics:
- name: Test WER
type: wer
value: 29.97
- name: Test CER
type: cer
value: NA
---
<!-- 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. -->
# wav2vec2-large-xls-r-300m-finnish
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - FI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2307
- Wer: 0.2984
## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 70.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9032 | 4.39 | 500 | 2.8768 | 1.0 |
| 1.5724 | 8.77 | 1000 | 0.5638 | 0.6438 |
| 1.1818 | 13.16 | 1500 | 0.3338 | 0.4759 |
| 1.0798 | 17.54 | 2000 | 0.2876 | 0.4086 |
| 1.0296 | 21.93 | 2500 | 0.2694 | 0.4248 |
| 1.0014 | 26.32 | 3000 | 0.2626 | 0.3733 |
| 0.9616 | 30.7 | 3500 | 0.2391 | 0.3294 |
| 0.9303 | 35.09 | 4000 | 0.2352 | 0.3218 |
| 0.9248 | 39.47 | 4500 | 0.2351 | 0.3207 |
| 0.8837 | 43.86 | 5000 | 0.2341 | 0.3103 |
| 0.8887 | 48.25 | 5500 | 0.2311 | 0.3115 |
| 0.8529 | 52.63 | 6000 | 0.2230 | 0.3001 |
| 0.8404 | 57.02 | 6500 | 0.2279 | 0.3054 |
| 0.8242 | 61.4 | 7000 | 0.2298 | 0.3006 |
| 0.8288 | 65.79 | 7500 | 0.2333 | 0.2997 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
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