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RichardErkhov/
alonzogarbanzo_-_Bloom-1b7-ropes-Cont-IT-Step2-gguf

Name: alonzogarbanzo_-_Bloom-1b7-ropes-Cont-IT-Step2-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

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Bloom-1b7-ropes-Cont-IT-Step2 - GGUF

Model creator: https://huggingface.co/alonzogarbanzo/
Original model: https://huggingface.co/alonzogarbanzo/Bloom-1b7-ropes-Cont-IT-Step2/

Name	Quant method	Size
Bloom-1b7-ropes-Cont-IT-Step2.Q2_K.gguf	Q2_K	0.98GB
Bloom-1b7-ropes-Cont-IT-Step2.Q3_K_S.gguf	Q3_K_S	1.1GB
Bloom-1b7-ropes-Cont-IT-Step2.Q3_K.gguf	Q3_K	1.2GB
Bloom-1b7-ropes-Cont-IT-Step2.Q3_K_M.gguf	Q3_K_M	1.2GB
Bloom-1b7-ropes-Cont-IT-Step2.Q3_K_L.gguf	Q3_K_L	1.25GB
Bloom-1b7-ropes-Cont-IT-Step2.IQ4_XS.gguf	IQ4_XS	1.27GB
Bloom-1b7-ropes-Cont-IT-Step2.Q4_0.gguf	Q4_0	1.31GB
Bloom-1b7-ropes-Cont-IT-Step2.IQ4_NL.gguf	IQ4_NL	1.31GB
Bloom-1b7-ropes-Cont-IT-Step2.Q4_K_S.gguf	Q4_K_S	1.31GB
Bloom-1b7-ropes-Cont-IT-Step2.Q4_K.gguf	Q4_K	1.39GB
Bloom-1b7-ropes-Cont-IT-Step2.Q4_K_M.gguf	Q4_K_M	1.39GB
Bloom-1b7-ropes-Cont-IT-Step2.Q4_1.gguf	Q4_1	1.41GB
Bloom-1b7-ropes-Cont-IT-Step2.Q5_0.gguf	Q5_0	1.51GB
Bloom-1b7-ropes-Cont-IT-Step2.Q5_K_S.gguf	Q5_K_S	1.51GB
Bloom-1b7-ropes-Cont-IT-Step2.Q5_K.gguf	Q5_K	1.57GB
Bloom-1b7-ropes-Cont-IT-Step2.Q5_K_M.gguf	Q5_K_M	1.57GB
Bloom-1b7-ropes-Cont-IT-Step2.Q5_1.gguf	Q5_1	1.61GB
Bloom-1b7-ropes-Cont-IT-Step2.Q6_K.gguf	Q6_K	1.72GB
Bloom-1b7-ropes-Cont-IT-Step2.Q8_0.gguf	Q8_0	2.23GB

Original model description:

license: bigscience-bloom-rail-1.0 base_model: alonzogarbanzo/Bloom-1b7-winograd-wsc-IT-baseline tags:

generated_from_trainer model-index:
name: Bloom-1b7-ropes-Cont-IT-Step2 results: []

Bloom-1b7-ropes-Cont-IT-Step2

This model is a fine-tuned version of alonzogarbanzo/Bloom-1b7-winograd-wsc-IT-baseline 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: 5e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Final Results: {'loss': 0.0261, 'grad_norm': 1.9494764804840088, 'learning_rate': 3.0000000000000004e-07, 'epoch': 10.0}

Average Results: {'train_runtime': 858.2936, 'train_samples_per_second': 2.33, 'train_steps_per_second': 0.583, 'train_loss': 0.4610937827527523, 'epoch': 10.0}

Framework versions

Transformers 4.38.1
Pytorch 2.2.0+cu121
Datasets 2.17.0
Tokenizers 0.15.2

RichardErkhov/alonzogarbanzo_-_Bloom-1b7-ropes-Cont-IT-Step2-gguf

Original model description:

Bloom-1b7-ropes-Cont-IT-Step2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
alonzogarbanzo_-_Bloom-1b7-ropes-Cont-IT-Step2-gguf