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RichardErkhov/
tsavage68_-_IE_M2_1000steps_1e5rate_01beta_cSFTDPO-gguf

Name: tsavage68_-_IE_M2_1000steps_1e5rate_01beta_cSFTDPO-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

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IE_M2_1000steps_1e5rate_01beta_cSFTDPO - GGUF

Model creator: https://huggingface.co/tsavage68/
Original model: https://huggingface.co/tsavage68/IE_M2_1000steps_1e5rate_01beta_cSFTDPO/

Name	Quant method	Size
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q2_K.gguf	Q2_K	2.53GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.IQ3_XS.gguf	IQ3_XS	2.81GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.IQ3_S.gguf	IQ3_S	2.96GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q3_K_S.gguf	Q3_K_S	2.95GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.IQ3_M.gguf	IQ3_M	3.06GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q3_K.gguf	Q3_K	3.28GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q3_K_M.gguf	Q3_K_M	3.28GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q3_K_L.gguf	Q3_K_L	3.56GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.IQ4_XS.gguf	IQ4_XS	3.67GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q4_0.gguf	Q4_0	3.83GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.IQ4_NL.gguf	IQ4_NL	3.87GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q4_K_S.gguf	Q4_K_S	3.86GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q4_K.gguf	Q4_K	4.07GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q4_K_M.gguf	Q4_K_M	4.07GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q4_1.gguf	Q4_1	4.24GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q5_0.gguf	Q5_0	4.65GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q5_K_S.gguf	Q5_K_S	4.65GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q5_K.gguf	Q5_K	4.78GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q5_K_M.gguf	Q5_K_M	4.78GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q5_1.gguf	Q5_1	5.07GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q6_K.gguf	Q6_K	5.53GB
IE_M2_1000steps_1e5rate_01beta_cSFTDPO.Q8_0.gguf	Q8_0	7.17GB

Original model description:

library_name: transformers license: apache-2.0 base_model: tsavage68/IE_M2_1000steps_1e7rate_SFT tags:

trl
dpo
generated_from_trainer model-index:
name: IE_M2_1000steps_1e5rate_01beta_cSFTDPO results: []

IE_M2_1000steps_1e5rate_01beta_cSFTDPO

This model is a fine-tuned version of tsavage68/IE_M2_1000steps_1e7rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3743
Rewards/chosen: -2.2787
Rewards/rejected: -22.2937
Rewards/accuracies: 0.4600
Rewards/margins: 20.0150
Logps/rejected: -263.9586
Logps/chosen: -64.9924
Logits/rejected: -2.7884
Logits/chosen: -2.7491

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: 1e-05
train_batch_size: 2
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.4505	0.4	50	0.3743	-2.1144	-14.8883	0.4600	12.7739	-189.9051	-63.3497	-2.7726	-2.7468
0.3812	0.8	100	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3119	1.2	150	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3639	1.6	200	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.4332	2.0	250	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3986	2.4	300	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3986	2.8	350	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.4505	3.2	400	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.4505	3.6	450	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.4332	4.0	500	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3292	4.4	550	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3639	4.8	600	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.4505	5.2	650	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.4505	5.6	700	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3639	6.0	750	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.2426	6.4	800	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.5025	6.8	850	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3119	7.2	900	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3466	7.6	950	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491
0.3812	8.0	1000	0.3743	-2.2787	-22.2937	0.4600	20.0150	-263.9586	-64.9924	-2.7884	-2.7491

Framework versions

Transformers 4.44.2
Pytorch 2.0.0+cu117
Datasets 3.0.0
Tokenizers 0.19.1

RichardErkhov/tsavage68_-_IE_M2_1000steps_1e5rate_01beta_cSFTDPO-gguf

Original model description:

IE_M2_1000steps_1e5rate_01beta_cSFTDPO

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
tsavage68_-_IE_M2_1000steps_1e5rate_01beta_cSFTDPO-gguf