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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: BEE-spoke-data/tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024
tags:
- generated_from_trainer
model-index:
- name: tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024-infinity-instruct-7m-T2T_en-1024-v2
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. -->
# tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024-infinity-instruct-7m-T2T_en-1024-v2
This model is a fine-tuned version of [BEE-spoke-data/tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024](https://huggingface.co/BEE-spoke-data/tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024) on the pszemraj/infinity-instruct-7m-T2T_en dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1159
- Num Input Tokens Seen: 810839096
## 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: 6969
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Input Tokens Seen |
|:-------------:|:------:|:-----:|:---------------:|:-----------------:|
| 1.234 | 0.0969 | 2000 | 1.2439 | 78067836 |
| 1.2248 | 0.1938 | 4000 | 1.2256 | 156868756 |
| 1.2024 | 0.2907 | 6000 | 1.2009 | 235148092 |
| 1.2074 | 0.3876 | 8000 | 1.1777 | 313452856 |
| 1.1617 | 0.4845 | 10000 | 1.1597 | 392316428 |
| 1.1755 | 0.5815 | 12000 | 1.1437 | 471101508 |
| 1.1473 | 0.6784 | 14000 | 1.1321 | 549831184 |
| 1.1743 | 0.7753 | 16000 | 1.1244 | 628937800 |
| 1.137 | 0.8722 | 18000 | 1.1179 | 707117360 |
| 1.0713 | 0.9691 | 20000 | 1.1160 | 785755388 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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